From ea1c74eb6e1c8b4937ab6173276ea6ca83826ee0 Mon Sep 17 00:00:00 2001 From: simplify <39580716+simplify23@users.noreply.github.com> Date: Tue, 25 Jul 2023 09:21:50 +0800 Subject: [PATCH 1/2] Update README.md --- README.md | 407 +++++++++++++++++++++++++++--------------------------- 1 file changed, 205 insertions(+), 202 deletions(-) diff --git a/README.md b/README.md index 8c3d114..11e5278 100644 --- a/README.md +++ b/README.md @@ -32,84 +32,85 @@ This repository is maintained by Massimo Caccia and Timothée Lesort don't hesit - [Workshops](https://github.com/optimass/continual_learning_papers/blob/master/README.md#workshops) ## Classics -- [**Catastrophic forgetting in connectionist networks**](https://www.sciencedirect.com/science/article/abs/pii/S1364661399012942) , (1999) by *French, Robert M.* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1335-L1349) -- [**Lifelong robot learning**](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.71.3723&rep=rep1&type=pdf) , (1995) by *Thrun, Sebastian and Mitchell, Tom M* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L423-L432) +- [**Catastrophic forgetting in connectionist networks**](https://www.sciencedirect.com/science/article/abs/pii/S1364661399012942) , (1999) by *French, Robert M.* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1353-L1367) +- [**Lifelong robot learning**](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.71.3723&rep=rep1&type=pdf) , (1995) by *Thrun, Sebastian and Mitchell, Tom M* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L441-L450) ``` Argues knowledge transfer is essential if robots are to learn control with moderate learning times ``` -- [**Catastrophic Forgetting, Rehearsal and Pseudorehearsal**](https://doi.org/10.1080/09540099550039318) , (1995) by * Anthony Robins * [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2075-L2088) -- [**Catastrophic interference in connectionist networks: The sequential learning problem**](https://www.sciencedirect.com/science/article/pii/S0079742108605368) , (1989) by *McCloskey, Michael and Cohen, Neal J* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1015-L1025) +- [**Catastrophic Forgetting, Rehearsal and Pseudorehearsal**](https://doi.org/10.1080/09540099550039318) , (1995) by * Anthony Robins * [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2093-L2106) +- [**Catastrophic interference in connectionist networks: The sequential learning problem**](https://www.sciencedirect.com/science/article/pii/S0079742108605368) , (1989) by *McCloskey, Michael and Cohen, Neal J* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1033-L1043) ``` Introduces CL and reveals the catastrophic forgetting problem ``` ## Empirical Study -- [**Effects of Auxiliary Knowledge on Continual Learning**](https://arxiv.org/abs/2206.02577) , (ICPR 2022) by *Bellitto, Giovanni, Pennisi, Matteo, Palazzo, Simone, Bonicelli, Lorenzo, Boschini, Matteo, Calderara, Simone and Spampinato, Concetto* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L158-L165) -- [**Rethinking Experience Replay: a Bag of Tricks for Continual Learning**](https://ieeexplore.ieee.org/abstract/document/9412614) , (ICPR 2021) by *Buzzega, Pietro, Boschini, Matteo, Porrello, Angelo and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L257-L268) -- [**A comprehensive study of class incremental learning algorithms for visual tasks**](https://www.sciencedirect.com/science/article/pii/S0893608020304202) , (Neural Networks 2021) by *Eden Belouadah, Adrian Popescu and Ioannis Kanellos* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2808-L2820) -- **Online Continual Learning in Image Classification: An Empirical Survey**, (2021) by *Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim and Scott Sanner* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2822-L2830) -- **GDumb: A simple approach that questions our progress in continual learning**, (ECCV 2020) by *Prabhu, Ameya, Torr, Philip HS and Dokania, Puneet K* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L282-L290) +- [**Effects of Auxiliary Knowledge on Continual Learning**](https://arxiv.org/abs/2206.02577) , (ICPR 2022) by *Bellitto, Giovanni, Pennisi, Matteo, Palazzo, Simone, Bonicelli, Lorenzo, Boschini, Matteo, Calderara, Simone and Spampinato, Concetto* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L176-L183) +- [**Rethinking Experience Replay: a Bag of Tricks for Continual Learning**](https://ieeexplore.ieee.org/abstract/document/9412614) , (ICPR 2021) by *Buzzega, Pietro, Boschini, Matteo, Porrello, Angelo and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L275-L286) +- [**A comprehensive study of class incremental learning algorithms for visual tasks**](https://www.sciencedirect.com/science/article/pii/S0893608020304202) , (Neural Networks 2021) by *Eden Belouadah, Adrian Popescu and Ioannis Kanellos* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2826-L2838) +- **Online Continual Learning in Image Classification: An Empirical Survey**, (2021) by *Zheda Mai, Ruiwen Li, Jihwan Jeong, David Quispe, Hyunwoo Kim and Scott Sanner* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2840-L2848) +- **GDumb: A simple approach that questions our progress in continual learning**, (ECCV 2020) by *Prabhu, Ameya, Torr, Philip HS and Dokania, Puneet K* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L300-L308) ``` introduces a super simple methods that outperforms almost all methods in all of the CL benchmarks. We need new better benchamrks ``` -- [**Continual learning: A comparative study on how to defy forgetting in classification tasks**](https://arxiv.org/abs/1909.08383) , (2019) by *Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Ales Leonardis, Gregory Slabaugh and Tinne Tuytelaars* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L508-L517) +- [**Continual learning: A comparative study on how to defy forgetting in classification tasks**](https://arxiv.org/abs/1909.08383) , (2019) by *Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Ales Leonardis, Gregory Slabaugh and Tinne Tuytelaars* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L526-L535) ``` Extensive empirical study of CL methods (in the multi-head setting) ``` -- [**Three scenarios for continual learning**](https://arxiv.org/abs/1904.07734) , (arXiv 2019) by *van de Ven, Gido M and Tolias, Andreas S* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1047-L1054) +- [**Three scenarios for continual learning**](https://arxiv.org/abs/1904.07734) , (arXiv 2019) by *van de Ven, Gido M and Tolias, Andreas S* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1065-L1072) ``` An extensive review of CL methods in three different scenarios (task-, domain-, and class-incremental learning) ``` -- **Continuous learning in single-incremental-task scenarios**, (Neural Networks 2019) by *Maltoni, Davide and Lomonaco, Vincenzo* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1362-L1371) -- [**Towards Robust Evaluations of Continual Learning**](https://arxiv.org/abs/1805.09733) , (arXiv 2018) by *Farquhar, Sebastian and Gal, Yarin* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L435-L442) +- **Continuous learning in single-incremental-task scenarios**, (Neural Networks 2019) by *Maltoni, Davide and Lomonaco, Vincenzo* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1380-L1389) +- [**Towards Robust Evaluations of Continual Learning**](https://arxiv.org/abs/1805.09733) , (arXiv 2018) by *Farquhar, Sebastian and Gal, Yarin* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L453-L460) ``` Proposes desideratas and reexamines the evaluation protocol ``` -- **Catastrophic forgetting: still a problem for DNNs**, (ICANN 2018) by *Pf\"ulb, B, Gepperth, A, Abdullah, S and Krawczyk, A* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2226-L2232) +- **Catastrophic forgetting: still a problem for DNNs**, (ICANN 2018) by *Pf\"ulb, B, Gepperth, A, Abdullah, S and Krawczyk, A* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2244-L2250) - **Measuring Catastrophic Forgetting in Neural Networks**, (2017) by *Kemker, R., McClure, M., Abitino, A. and Hayes, T. and -Kanan, C.* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1374-L1387) -- [**CORe50: a New Dataset and Benchmark for Continuous Object Recognition**](http://proceedings.mlr.press/v78/lomonaco17a.html) , (CoRL 2017) by *Vincenzo Lomonaco and Davide Maltoni* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1389-L1404) -- [**An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks**](https://arxiv.org/abs/1312.6211) , (2013) by *Goodfellow, I.~J., Mirza, M., Xiao, D., Courville, A. and Bengio, Y.* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L492-L505) +Kanan, C.* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1392-L1405) +- [**CORe50: a New Dataset and Benchmark for Continuous Object Recognition**](http://proceedings.mlr.press/v78/lomonaco17a.html) , (CoRL 2017) by *Vincenzo Lomonaco and Davide Maltoni* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1407-L1422) +- [**An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks**](https://arxiv.org/abs/1312.6211) , (2013) by *Goodfellow, I.~J., Mirza, M., Xiao, D., Courville, A. and Bengio, Y.* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L510-L523) ``` Investigates CF in neural networks ``` ## Surveys -- [**An Investigation of Replay-based Approaches for Continual Learning**](https://arxiv.org/abs/2108.06758) , (IJCNN 2021) by *Bagus, Benedikt and Gepperth, Alexander* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3295-L3304) -- **Embracing Change: Continual Learning in Deep Neural Networks**, (2020) by *Hadsell, Raia, Rao, Dushyant, Rusu, Andrei and Pascanu, Razvan* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L167-L177) -- **Towards Continual Reinforcement Learning: A Review and Perspectives**, (2020) by *Khimya Khetarpal, Matthew Riemer, Irina Rish and Doina Precup* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L293-L301) +- [**An Investigation of Replay-based Approaches for Continual Learning**](https://arxiv.org/abs/2108.06758) , (IJCNN 2021) by *Bagus, Benedikt and Gepperth, Alexander* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3313-L3322) +- **Embracing Change: Continual Learning in Deep Neural Networks**, (2020) by *Hadsell, Raia, Rao, Dushyant, Rusu, Andrei and Pascanu, Razvan* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L185-L195) +- **Towards Continual Reinforcement Learning: A Review and Perspectives**, (2020) by *Khimya Khetarpal, Matthew Riemer, Irina Rish and Doina Precup* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L311-L319) ``` A review on continual reinforcement learning ``` -- [**Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges**](http://www.sciencedirect.com/science/article/pii/S1566253519307377) , (Information Fusion 2020) by *Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat and Natalia Díaz-Rodríguez* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1321-L1332) -- [**A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning**](https://arxiv.org/abs/2009.01797) , (arXiv 2020) by *Mundt, Martin, Hong, Yong Won, Pliushch, Iuliia and Ramesh, Visvanathan* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2595-L2602) +- [**Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges**](http://www.sciencedirect.com/science/article/pii/S1566253519307377) , (Information Fusion 2020) by *Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat and Natalia Díaz-Rodríguez* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1339-L1350) +- [**A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning**](https://arxiv.org/abs/2009.01797) , (arXiv 2020) by *Mundt, Martin, Hong, Yong Won, Pliushch, Iuliia and Ramesh, Visvanathan* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2613-L2620) ``` propose a consolidated view to bridge continual learning, active learning and open set recognition in DNNs ``` -- [**Continual Lifelong Learning in Natural Language Processing: A Survey**](https://www.aclweb.org/anthology/2020.coling-main.574) , (2020) by *Magdalena Biesialska, Katarzyna Biesialska, Marta R. Costa-jussà* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2773-L2785) +- [**Continual Lifelong Learning in Natural Language Processing: A Survey**](https://www.aclweb.org/anthology/2020.coling-main.574) , (2020) by *Magdalena Biesialska, Katarzyna Biesialska, Marta R. Costa-jussà* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2791-L2803) ``` An extensive review of CL in Natural Language Processing (NLP) ``` -- [**Continual lifelong learning with neural networks: A review**](http://www.sciencedirect.com/science/article/pii/S0893608019300231) , (Neural Networks 2019) by *German I. Parisi, Ronald Kemker, Jose L. Part, Christopher Kanan and Stefan Wermter* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L520-L531) +- [**Continual lifelong learning with neural networks: A review**](http://www.sciencedirect.com/science/article/pii/S0893608019300231) , (Neural Networks 2019) by *German I. Parisi, Ronald Kemker, Jose L. Part, Christopher Kanan and Stefan Wermter* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L538-L549) ``` An extensive review of CL ``` -- [**Incremental learning algorithms and applications**](https://hal.archives-ouvertes.fr/hal-01418129) , (2016) by *Gepperth, Alexander and Hammer, Barbara* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1178-L1189) +- [**Incremental learning algorithms and applications**](https://hal.archives-ouvertes.fr/hal-01418129) , (2016) by *Gepperth, Alexander and Hammer, Barbara* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1196-L1207) ``` A survey on incremental learning and the various applications fields ``` ## Influentials -- [**Efficient Lifelong Learning with A-GEM**](https://arxiv.org/abs/1812.00420) , (ICLR 2019) by *Chaudhry, Arslan, Ranzato, Marc’Aurelio, Rohrbach, Marcus and Elhoseiny, Mohamed* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L445-L452) +- [**Efficient Lifelong Learning with A-GEM**](https://arxiv.org/abs/1812.00420) , (ICLR 2019) by *Chaudhry, Arslan, Ranzato, Marc’Aurelio, Rohrbach, Marcus and Elhoseiny, Mohamed* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L463-L470) ``` More efficient GEM; Introduces online continual learning ``` -- [**Towards Robust Evaluations of Continual Learning**](https://arxiv.org/abs/1805.09733) , (arXiv 2018) by *Farquhar, Sebastian and Gal, Yarin* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L435-L442) +- [**Towards Robust Evaluations of Continual Learning**](https://arxiv.org/abs/1805.09733) , (arXiv 2018) by *Farquhar, Sebastian and Gal, Yarin* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L453-L460) ``` Proposes desideratas and reexamines the evaluation protocol ``` -- [**Continual Learning in Practice**](https://arxiv.org/abs/1903.05202) , (NeurIPS Workshop 2018) by *Diethe, Tom, Borchert, Tom, Thereska, Eno, Pigem, Borja de Balle and Lawrence, Neil* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2327-L2334) +- [**Continual Learning in Practice**](https://arxiv.org/abs/1903.05202) , (NeurIPS Workshop 2018) by *Diethe, Tom, Borchert, Tom, Thereska, Eno, Pigem, Borja de Balle and Lawrence, Neil* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2345-L2352) ``` Proposes a reference architecture for a continual learning system ``` -- [**Overcoming catastrophic forgetting in neural networks**](https://www.pnas.org/content/pnas/114/13/3521.full.pdf) , (PNAS 2017) by *Kirkpatrick, James, Pascanu, Razvan, Rabinowitz, Neil, Veness, Joel, Desjardins, Guillaume, Rusu, Andrei A, Milan, Kieran, Quan, John, Ramalho, Tiago, Grabska-Barwinska, Agnieszka and others* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L455-L463) -- [**Gradient Episodic Memory for Continual Learning**](http://papers.nips.cc/paper/7225-gradient-episodic-memory-for-continual-learning.pdf) , (NeurIPS 2017) by *Lopez-Paz, David and Ranzato, Marc-Aurelio* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L467-L477) +- [**Overcoming catastrophic forgetting in neural networks**](https://www.pnas.org/content/pnas/114/13/3521.full.pdf) , (PNAS 2017) by *Kirkpatrick, James, Pascanu, Razvan, Rabinowitz, Neil, Veness, Joel, Desjardins, Guillaume, Rusu, Andrei A, Milan, Kieran, Quan, John, Ramalho, Tiago, Grabska-Barwinska, Agnieszka and others* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L473-L481) +- [**Gradient Episodic Memory for Continual Learning**](http://papers.nips.cc/paper/7225-gradient-episodic-memory-for-continual-learning.pdf) , (NeurIPS 2017) by *Lopez-Paz, David and Ranzato, Marc-Aurelio* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L485-L495) ``` A model that alliviates CF via constrained optimization ``` -- [**Continual learning with deep generative replay**](https://arxiv.org/abs/1705.08690) , (NeurIPS 2017) by *Shin, Hanul, Lee, Jung Kwon, Kim, Jaehong and Kim, Jiwon* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L481-L489) +- [**Continual learning with deep generative replay**](https://arxiv.org/abs/1705.08690) , (NeurIPS 2017) by *Shin, Hanul, Lee, Jung Kwon, Kim, Jaehong and Kim, Jiwon* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L499-L507) ``` Introduces generative replay ``` -- [**An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks**](https://arxiv.org/abs/1312.6211) , (2013) by *Goodfellow, I.~J., Mirza, M., Xiao, D., Courville, A. and Bengio, Y.* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L492-L505) +- [**An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks**](https://arxiv.org/abs/1312.6211) , (2013) by *Goodfellow, I.~J., Mirza, M., Xiao, D., Courville, A. and Bengio, Y.* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L510-L523) ``` Investigates CF in neural networks ``` ## New Settings or Metrics -- [**IIRC: Incremental Implicitly-Refined Classification**](https://chandar-lab.github.io/IIRC/) , (CVPR 2021) by *Mohamed Abdelsalam, Mojtaba Faramarzi, Shagun Sodhani and Sarath Chandar* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2761-L2769) +- [**MRN: Multiplexed Routing Network for Incremental Multilingual Text Recognition**](https://arxiv.org/abs/2305.14758) , (ICCV 2023) by *Zheng, Tianlun, Chen, Zhineng, Huang, BingChen, Zhang, Wei and Jiang, Yu-Gang* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L19-L26) +- [**IIRC: Incremental Implicitly-Refined Classification**](https://chandar-lab.github.io/IIRC/) , (CVPR 2021) by *Mohamed Abdelsalam, Mojtaba Faramarzi, Shagun Sodhani and Sarath Chandar* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2779-L2787) ``` A setup and benchmark to evaluate lifelong learning models in more real-life aligned scenarios. ``` -- [**Sequoia - Towards a Systematic Organization of Continual Learning Research**](https://github.com/lebrice/Sequoia) , (2021) by *Fabrice Normandin, Florian Golemo, Oleksiy Ostapenko, Matthew Riemer, Pau Rodriguez, Julio Hurtado, Khimya Khetarpal, Timothée Lesort, Laurent Charlin, Irina Rish and Massimo Caccia* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2951-L2960) +- [**Sequoia - Towards a Systematic Organization of Continual Learning Research**](https://github.com/lebrice/Sequoia) , (2021) by *Fabrice Normandin, Florian Golemo, Oleksiy Ostapenko, Matthew Riemer, Pau Rodriguez, Julio Hurtado, Khimya Khetarpal, Timothée Lesort, Laurent Charlin, Irina Rish and Massimo Caccia* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2969-L2978) ``` A library that unifies Continual Supervised and Continual Reinforcement Learning research ``` -- [**Wandering Within a World: Online Contextualized Few-Shot Learning**](https://arxiv.org/abs/2007.04546) , (2020) by *Mengye Ren, Michael L. Iuzzolino, Michael C. Mozer and Richard S. Zemel* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L325-L333) +- [**Wandering Within a World: Online Contextualized Few-Shot Learning**](https://arxiv.org/abs/2007.04546) , (2020) by *Mengye Ren, Michael L. Iuzzolino, Michael C. Mozer and Richard S. Zemel* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L343-L351) ``` proposes a new continual few-shot setting where spacial and temporal context can be leveraged to and unseen classes need to be predicted ``` -- [**Defining Benchmarks for Continual Few-Shot Learning**](https://arxiv.org/abs/2004.11967) , (arXiv 2020) by *Antoniou, Antreas, Patacchiola, Massimiliano, Ochal, Mateusz and Storkey, Amos* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L367-L374) +- [**Defining Benchmarks for Continual Few-Shot Learning**](https://arxiv.org/abs/2004.11967) , (arXiv 2020) by *Antoniou, Antreas, Patacchiola, Massimiliano, Ochal, Mateusz and Storkey, Amos* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L385-L392) ``` (title is a good enough summary) ``` -- [**Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning**](https://arxiv.org/abs/2003.05856) , (2020) by *Caccia, Massimo, Rodriguez, Pau, Ostapenko, Oleksiy, Normandin, Fabrice, Lin, Min, Caccia, Lucas, Laradji, Issam, Rish, Irina, Lacoste, Alexandre, Vazquez, David and Charlin, Laurent* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1473-L1480) +- [**Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning**](https://arxiv.org/abs/2003.05856) , (2020) by *Caccia, Massimo, Rodriguez, Pau, Ostapenko, Oleksiy, Normandin, Fabrice, Lin, Min, Caccia, Lucas, Laradji, Issam, Rish, Irina, Lacoste, Alexandre, Vazquez, David and Charlin, Laurent* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1491-L1498) ``` Proposes a new approach to CL evaluation more aligned with real-life applications, bringing CL closer to Online Learning and Open-World learning ``` -- [**Compositional Language Continual Learning**](https://openreview.net/forum?id=rklnDgHtDS) , (ICLR 2020) by *Yuanpeng Li, Liang Zhao, Kenneth Church and Mohamed Elhoseiny* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1551-L1558) +- [**Compositional Language Continual Learning**](https://openreview.net/forum?id=rklnDgHtDS) , (ICLR 2020) by *Yuanpeng Li, Liang Zhao, Kenneth Church and Mohamed Elhoseiny* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1569-L1576) ``` method for compositional continual learning of sequence-to-sequence models ``` -- [**A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning**](https://arxiv.org/abs/2009.01797) , (arXiv 2020) by *Mundt, Martin, Hong, Yong Won, Pliushch, Iuliia and Ramesh, Visvanathan* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2595-L2602) +- [**A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning**](https://arxiv.org/abs/2009.01797) , (arXiv 2020) by *Mundt, Martin, Hong, Yong Won, Pliushch, Iuliia and Ramesh, Visvanathan* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2613-L2620) ``` propose a consolidated view to bridge continual learning, active learning and open set recognition in DNNs ``` -- **Don't forget, there is more than forgetting: new metrics for Continual Learning**, (arXiv 2018) by *D{\'\i}az-Rodr{\'\i}guez, Natalia, Lomonaco, Vincenzo, Filliat, David and Maltoni, Davide* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2942-L2948) +- **Don't forget, there is more than forgetting: new metrics for Continual Learning**, (arXiv 2018) by *D{\'\i}az-Rodr{\'\i}guez, Natalia, Lomonaco, Vincenzo, Filliat, David and Maltoni, Davide* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2960-L2966) ``` introduces a CL score that takes more than just forgetting into account ``` ## General Continual Learning Methods (SL and RL) -- [**Overcoming catastrophic forgetting in neural networks**](https://www.pnas.org/content/pnas/114/13/3521.full.pdf) , (PNAS 2017) by *Kirkpatrick, James, Pascanu, Razvan, Rabinowitz, Neil, Veness, Joel, Desjardins, Guillaume, Rusu, Andrei A, Milan, Kieran, Quan, John, Ramalho, Tiago, Grabska-Barwinska, Agnieszka and others* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L455-L463) +- [**Overcoming catastrophic forgetting in neural networks**](https://www.pnas.org/content/pnas/114/13/3521.full.pdf) , (PNAS 2017) by *Kirkpatrick, James, Pascanu, Razvan, Rabinowitz, Neil, Veness, Joel, Desjardins, Guillaume, Rusu, Andrei A, Milan, Kieran, Quan, John, Ramalho, Tiago, Grabska-Barwinska, Agnieszka and others* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L473-L481) - [**PathNet: Evolution Channels Gradient Descent in Super Neural Networks**](http://arxiv.org/abs/1701.08734) , (2017) by *Chrisantha Fernando and Dylan Banarse and Charles Blundell and @@ -117,161 +118,162 @@ Yori Zwols and David Ha and Andrei A. Rusu and Alexander Pritzel and -Daan Wierstra* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1796-L1816) +Daan Wierstra* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1814-L1834) ## Task-Agnostic Continual Learning -- [**Task-agnostic Continual Learning with Hybrid Probabilistic Models**](https://arxiv.org/abs/2106.12772) , (2021) by *Polina Kirichenko, Mehrdad Farajtabar, Dushyant Rao, Balaji Lakshminarayanan, Nir Levine, Ang Li, Huiyi Hu, Andrew Gordon Wilson and Razvan Pascanu* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L226-L235) -- [**Learning where to learn: Gradient sparsity in meta and continual learning**](https://proceedings.neurips.cc/paper/2021/hash/2a10665525774fa2501c2c8c4985ce61-Abstract.html) , (2021) by *Von Oswald, Johannes, Zhao, Dominic, Kobayashi, Seijin, Schug, Simon, Caccia, Massimo, Zucchet, Nicolas and Sacramento, Jo{\~a}o* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L247-L255) -- [**Uncertainty-guided Continual Learning with Bayesian Neural Networks**](https://openreview.net/forum?id=HklUCCVKDB) , (ICLR 2020) by *Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell and Marcus Rohrbach* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L557-L564) +- [**Task-agnostic Continual Learning with Hybrid Probabilistic Models**](https://arxiv.org/abs/2106.12772) , (2021) by *Polina Kirichenko, Mehrdad Farajtabar, Dushyant Rao, Balaji Lakshminarayanan, Nir Levine, Ang Li, Huiyi Hu, Andrew Gordon Wilson and Razvan Pascanu* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L244-L253) +- [**Learning where to learn: Gradient sparsity in meta and continual learning**](https://proceedings.neurips.cc/paper/2021/hash/2a10665525774fa2501c2c8c4985ce61-Abstract.html) , (2021) by *Von Oswald, Johannes, Zhao, Dominic, Kobayashi, Seijin, Schug, Simon, Caccia, Massimo, Zucchet, Nicolas and Sacramento, Jo{\~a}o* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L265-L273) +- [**Uncertainty-guided Continual Learning with Bayesian Neural Networks**](https://openreview.net/forum?id=HklUCCVKDB) , (ICLR 2020) by *Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell and Marcus Rohrbach* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L575-L582) ``` Uses Bayes by Backprop for variational Continual Learning. ``` -- [**Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning**](https://arxiv.org/abs/2003.05856) , (2020) by *Caccia, Massimo, Rodriguez, Pau, Ostapenko, Oleksiy, Normandin, Fabrice, Lin, Min, Caccia, Lucas, Laradji, Issam, Rish, Irina, Lacoste, Alexandre, Vazquez, David and Charlin, Laurent* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1473-L1480) +- [**Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning**](https://arxiv.org/abs/2003.05856) , (2020) by *Caccia, Massimo, Rodriguez, Pau, Ostapenko, Oleksiy, Normandin, Fabrice, Lin, Min, Caccia, Lucas, Laradji, Issam, Rish, Irina, Lacoste, Alexandre, Vazquez, David and Charlin, Laurent* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1491-L1498) ``` Proposes a new approach to CL evaluation more aligned with real-life applications, bringing CL closer to Online Learning and Open-World learning ``` -- **iTAML: An Incremental Task-Agnostic Meta-learning Approach**, (CVPR 2020) by *Rajasegaran, Jathushan, Khan, Salman, Hayat, Munawar, Khan, Fahad Shahbaz and Shah, Mubarak* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2411-L2418) -- [**Continual Unsupervised Representation Learning**](https://arxiv.org/pdf/1910.14481.pdf) , (2019) by *Dushyant Rao, Francesco Visin, Andrei A. Rusu, Yee Whye Teh, Razvan Pascanu and Raia Hadsell* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L942-L951) +- **iTAML: An Incremental Task-Agnostic Meta-learning Approach**, (CVPR 2020) by *Rajasegaran, Jathushan, Khan, Salman, Hayat, Munawar, Khan, Fahad Shahbaz and Shah, Mubarak* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2429-L2436) +- [**Continual Unsupervised Representation Learning**](https://arxiv.org/pdf/1910.14481.pdf) , (2019) by *Dushyant Rao, Francesco Visin, Andrei A. Rusu, Yee Whye Teh, Razvan Pascanu and Raia Hadsell* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L960-L969) ``` Introduces unsupervised continual learning (no task label and no task boundaries) ``` -- [**A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning**](https://arxiv.org/pdf/2001.00689.pdf) , (ICLR 2019) by *Lee, Soochan, Ha, Junsoo, Zhang, Dongsu and Kim, Gunhee* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1540-L1547) +- [**A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning**](https://arxiv.org/pdf/2001.00689.pdf) , (ICLR 2019) by *Lee, Soochan, Ha, Junsoo, Zhang, Dongsu and Kim, Gunhee* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1558-L1565) ``` This paper introduces expansion-based approach for task-free continual learning ``` -- [**Task Agnostic Continual Learning Using Online Variational Bayes**](https://arxiv.org/pdf/1803.10123.pdf) , (2018) by *Chen Zeno, Itay Golan, Elad Hoffer and Daniel Soudry* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L580-L589) +- [**Task Agnostic Continual Learning Using Online Variational Bayes**](https://arxiv.org/pdf/1803.10123.pdf) , (2018) by *Chen Zeno, Itay Golan, Elad Hoffer and Daniel Soudry* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L598-L607) ``` Introduces an optimizer for CL that relies on closed form updates of mu and sigma of BNN; introduce label trick for class learning (single-head) but warning: it isn't really task-agnostic ``` ## Regularization Methods -- [**Continual Learning in Deep Networks: an Analysis of the Last Layer**](https://arxiv.org/abs/2106.01834) , (arXiv 2021) by *Lesort, Timoth{\'e}e, George, Thomas and Rish, Irina* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3245-L3252) -- [**Continual Learning with Bayesian Neural Networks for Non-Stationary Data**](https://openreview.net/forum?id=SJlsFpVtDB) , (ICLR 2020) by *Richard Kurle, Botond Cseke, Alexej Klushyn, Patrick van der Smagt and Stephan Günnemann* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L888-L895) +- [**Continual Learning in Deep Networks: an Analysis of the Last Layer**](https://arxiv.org/abs/2106.01834) , (arXiv 2021) by *Lesort, Timoth{\'e}e, George, Thomas and Rish, Irina* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3263-L3270) +- [**Continual Learning with Bayesian Neural Networks for Non-Stationary Data**](https://openreview.net/forum?id=SJlsFpVtDB) , (ICLR 2020) by *Richard Kurle, Botond Cseke, Alexej Klushyn, Patrick van der Smagt and Stephan Günnemann* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L906-L913) ``` continual learning for non-stationary data using Bayesian neural networks and memory-based online variational Bayes ``` -- [**Improving and Understanding Variational Continual Learning**](https://arxiv.org/abs/1905.02099) , (2019) by *Siddharth Swaroop, Cuong V. Nguyen, Thang D. Bui and Richard E. Turner* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L545-L553) +- [**Improving and Understanding Variational Continual Learning**](https://arxiv.org/abs/1905.02099) , (2019) by *Siddharth Swaroop, Cuong V. Nguyen, Thang D. Bui and Richard E. Turner* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L563-L571) ``` Improved results and interpretation of VCL. ``` -- [**Uncertainty-based Continual Learning with Adaptive Regularization**](http://papers.nips.cc/paper/8690-uncertainty-based-continual-learning-with-adaptive-regularization.pdf) , (NeurIPS 2019) by *Ahn, Hongjoon, Cha, Sungmin, Lee, Donggyu and Moon, Taesup* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L567-L577) +- [**Uncertainty-based Continual Learning with Adaptive Regularization**](http://papers.nips.cc/paper/8690-uncertainty-based-continual-learning-with-adaptive-regularization.pdf) , (NeurIPS 2019) by *Ahn, Hongjoon, Cha, Sungmin, Lee, Donggyu and Moon, Taesup* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L585-L595) ``` Introduces VCL with uncertainty measured for neurons instead of weights. ``` -- [**Functional Regularisation for Continual Learning with Gaussian Processes**](https://arxiv.org/abs/1901.11356) , (ICLR 2019) by *Titsias, Michalis K, Schwarz, Jonathan, Matthews, Alexander G de G, Pascanu, Razvan and Teh, Yee Whye* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1351-L1358) +- [**Functional Regularisation for Continual Learning with Gaussian Processes**](https://arxiv.org/abs/1901.11356) , (ICLR 2019) by *Titsias, Michalis K, Schwarz, Jonathan, Matthews, Alexander G de G, Pascanu, Razvan and Teh, Yee Whye* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1369-L1376) ``` functional regularisation for Continual Learning: avoids forgetting a previous task by constructing and memorising an approximate posterior belief over the underlying task-specific function ``` -- [**Task Agnostic Continual Learning Using Online Variational Bayes**](https://arxiv.org/pdf/1803.10123.pdf) , (2018) by *Chen Zeno, Itay Golan, Elad Hoffer and Daniel Soudry* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L580-L589) +- [**Task Agnostic Continual Learning Using Online Variational Bayes**](https://arxiv.org/pdf/1803.10123.pdf) , (2018) by *Chen Zeno, Itay Golan, Elad Hoffer and Daniel Soudry* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L598-L607) ``` Introduces an optimizer for CL that relies on closed form updates of mu and sigma of BNN; introduce label trick for class learning (single-head) but warning: it isn't really task-agnostic ``` -- [**Overcoming Catastrophic Interference using Conceptor-Aided Backpropagation**](https://openreview.net/forum?id=B1al7jg0b) , (ICLR 2018) by *Xu He and Herbert Jaeger* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L621-L628) +- [**Overcoming Catastrophic Interference using Conceptor-Aided Backpropagation**](https://openreview.net/forum?id=B1al7jg0b) , (ICLR 2018) by *Xu He and Herbert Jaeger* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L639-L646) ``` Conceptor-Aided Backprop (CAB): gradients are shielded by conceptors against degradation of previously learned tasks ``` -- [**Overcoming Catastrophic Forgetting with Hard Attention to the Task**](http://proceedings.mlr.press/v80/serra18a.html) , (ICML 2018) by *Serra, Joan, Suris, Didac, Miron, Marius and Karatzoglou, Alexandros* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L641-L657) +- [**Overcoming Catastrophic Forgetting with Hard Attention to the Task**](http://proceedings.mlr.press/v80/serra18a.html) , (ICML 2018) by *Serra, Joan, Suris, Didac, Miron, Marius and Karatzoglou, Alexandros* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L659-L675) ``` Introducing a hard attention idea with binary masks ``` -- [**Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence**](https://arxiv.org/abs/1801.10112) , (ECCV 2018) by *Chaudhry, Arslan, Dokania, Puneet K, Ajanthan, Thalaiyasingam and Torr, Philip HS* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L660-L667) +- [**Riemannian Walk for Incremental Learning: Understanding Forgetting and Intransigence**](https://arxiv.org/abs/1801.10112) , (ECCV 2018) by *Chaudhry, Arslan, Dokania, Puneet K, Ajanthan, Thalaiyasingam and Torr, Philip HS* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L678-L685) ``` Formalizes the shortcomings of multi-head evaluation, as well as the importance of replay in single-head setup. Presenting an improved version of EWC. ``` -- [**Variational Continual Learning**](https://arxiv.org/abs/1710.10628) , (ICLR 2018) by *Cuong V. Nguyen, Yingzhen Li, Thang D. Bui and Richard E. Turner* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L691-L698) -- [**Progress \& compress: A scalable framework for continual learning**](https://arxiv.org/abs/1805.06370) , (ICML 2018) by *Schwarz, Jonathan, Luketina, Jelena, Czarnecki, Wojciech M, Grabska-Barwinska, Agnieszka, Teh, Yee Whye, Pascanu, Razvan and Hadsell, Raia* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L702-L709) +- [**Variational Continual Learning**](https://arxiv.org/abs/1710.10628) , (ICLR 2018) by *Cuong V. Nguyen, Yingzhen Li, Thang D. Bui and Richard E. Turner* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L709-L716) +- [**Progress \& compress: A scalable framework for continual learning**](https://arxiv.org/abs/1805.06370) , (ICML 2018) by *Schwarz, Jonathan, Luketina, Jelena, Czarnecki, Wojciech M, Grabska-Barwinska, Agnieszka, Teh, Yee Whye, Pascanu, Razvan and Hadsell, Raia* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L720-L727) ``` A new P\&C architecture; online EWC for keeping the knowledge about the previous task, knowledge for keeping the knowledge about the current task (Multi-head setting, RL) ``` -- **Online structured laplace approximations for overcoming catastrophic forgetting**, (NeurIPS 2018) by *Ritter, Hippolyt, Botev, Aleksandar and Barber, David* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2056-L2063) -- [**Facilitating Bayesian Continual Learning by Natural Gradients and Stein Gradients**](https://arxiv.org/abs/1904.10644) , (NeurIPS Workshop 2018) by *Chen, Yu, Diethe, Tom and Lawrence, Neil* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2337-L2344) +- **Online structured laplace approximations for overcoming catastrophic forgetting**, (NeurIPS 2018) by *Ritter, Hippolyt, Botev, Aleksandar and Barber, David* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2074-L2081) +- [**Facilitating Bayesian Continual Learning by Natural Gradients and Stein Gradients**](https://arxiv.org/abs/1904.10644) , (NeurIPS Workshop 2018) by *Chen, Yu, Diethe, Tom and Lawrence, Neil* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2355-L2362) ``` Improves on VCL ``` -- [**Overcoming catastrophic forgetting in neural networks**](https://www.pnas.org/content/pnas/114/13/3521.full.pdf) , (PNAS 2017) by *Kirkpatrick, James, Pascanu, Razvan, Rabinowitz, Neil, Veness, Joel, Desjardins, Guillaume, Rusu, Andrei A, Milan, Kieran, Quan, John, Ramalho, Tiago, Grabska-Barwinska, Agnieszka and others* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L455-L463) -- [**Memory Aware Synapses: Learning what (not) to forget**](http://arxiv.org/abs/1711.09601) , (2017) by *Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach and Tinne Tuytelaars* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L673-L686) +- [**Overcoming catastrophic forgetting in neural networks**](https://www.pnas.org/content/pnas/114/13/3521.full.pdf) , (PNAS 2017) by *Kirkpatrick, James, Pascanu, Razvan, Rabinowitz, Neil, Veness, Joel, Desjardins, Guillaume, Rusu, Andrei A, Milan, Kieran, Quan, John, Ramalho, Tiago, Grabska-Barwinska, Agnieszka and others* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L473-L481) +- [**Memory Aware Synapses: Learning what (not) to forget**](http://arxiv.org/abs/1711.09601) , (2017) by *Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach and Tinne Tuytelaars* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L691-L704) ``` Importance of parameter measured based on their contribution to change in the learned prediction function ``` -- [**Continual Learning Through Synaptic Intelligence**](http://proceedings.mlr.press/v70/zenke17a.html) , (ICML 2017) by *Zenke, Friedeman, Poole, Ben and Ganguli, Surya * [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L712-L727) +- [**Continual Learning Through Synaptic Intelligence**](http://proceedings.mlr.press/v70/zenke17a.html) , (ICML 2017) by *Zenke, Friedeman, Poole, Ben and Ganguli, Surya * [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L730-L745) ``` Synaptic Intelligence (SI). Importance of parameter measured based on their contribution to change in the loss. ``` -- **Overcoming catastrophic forgetting by incremental moment matching**, (NeurIPS 2017) by *Lee, Sang-Woo, Kim, Jin-Hwa, Jun, Jaehyun, Ha, Jung-Woo and Zhang, Byoung-Tak* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1925-L1932) +- **Overcoming catastrophic forgetting by incremental moment matching**, (NeurIPS 2017) by *Lee, Sang-Woo, Kim, Jin-Hwa, Jun, Jaehyun, Ha, Jung-Woo and Zhang, Byoung-Tak* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1943-L1950) ## Distillation Methods -- [**Class-Incremental Continual Learning into the eXtended DER-verse**](https://arxiv.org/abs/2201.00766) , (TPAMI 2022) by *Boschini, Matteo, Bonicelli, Lorenzo, Buzzega, Pietro, Porrello, Angelo and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L10-L19) -- [**Transfer without Forgetting**](https://arxiv.org/abs/2206.00388) , (ECCV 2022) by *Boschini, Matteo, Bonicelli, Lorenzo, Porrello, Angelo, Bellitto, Giovanni, Pennisi, Matteo, Palazzo, Simone, Spampinato, Concetto and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L46-L53) -- [**Self-Supervised Models are Continual Learners**](https://arxiv.org/abs/2112.04215) , (CVPR 2022) by *Fini, Enrico, da Costa, Victor G Turrisi, Alameda-Pineda, Xavier, Ricci, Elisa, Alahari, Karteek and Mairal, Julien* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3430-L3437) +- [**Class-Incremental Continual Learning into the eXtended DER-verse**](https://arxiv.org/abs/2201.00766) , (TPAMI 2022) by *Boschini, Matteo, Bonicelli, Lorenzo, Buzzega, Pietro, Porrello, Angelo and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L28-L37) +- [**Transfer without Forgetting**](https://arxiv.org/abs/2206.00388) , (ECCV 2022) by *Boschini, Matteo, Bonicelli, Lorenzo, Porrello, Angelo, Bellitto, Giovanni, Pennisi, Matteo, Palazzo, Simone, Spampinato, Concetto and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L64-L71) +- [**Self-Supervised Models are Continual Learners**](https://arxiv.org/abs/2112.04215) , (CVPR 2022) by *Fini, Enrico, da Costa, Victor G Turrisi, Alameda-Pineda, Xavier, Ricci, Elisa, Alahari, Karteek and Mairal, Julien* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3448-L3455) ``` Explores Continual Self-Supervised Learning and proposes a simple and effective feature distillation method ``` -- [**Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation**](https://arxiv.org/abs/2203.14098) , (TPAMI 2022) by *Yang, Guanglei, Fini, Enrico, Xu, Dan, Rota, Paolo, Ding, Mingli, Nabi, Moin, Alameda-Pineda, Xavier and Ricci, Elisa* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3440-L3448) -- [**Continual Attentive Fusion for Incremental Learning in Semantic Segmentation**](https://arxiv.org/abs/2202.00432) , (TMM 2022) by *Yang, Guanglei, Fini, Enrico, Xu, Dan, Rota, Paolo, Ding, Mingli, Hao, Tang, Alameda-Pineda, Xavier and Ricci, Elisa* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3450-L3458) -- [**Dark Experience for General Continual Learning: a Strong, Simple Baseline**](https://papers.nips.cc/paper/2020/file/b704ea2c39778f07c617f6b7ce480e9e-Paper.pdf) , (NeurIPS 2020) by *Buzzega, Pietro, Boschini, Matteo, Porrello, Angelo, Abati, Davide and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L270-L280) -- [**Online Continual Learning under Extreme Memory Constraints**](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123730715.pdf) , (ECCV 2020) by *Fini, Enrico, Lathuilière, Stèphane, Sangineto, Enver, Nabi, Moin and Ricci, Elisa* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2497-L2504) +- [**Uncertainty-aware Contrastive Distillation for Incremental Semantic Segmentation**](https://arxiv.org/abs/2203.14098) , (TPAMI 2022) by *Yang, Guanglei, Fini, Enrico, Xu, Dan, Rota, Paolo, Ding, Mingli, Nabi, Moin, Alameda-Pineda, Xavier and Ricci, Elisa* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3458-L3466) +- [**Continual Attentive Fusion for Incremental Learning in Semantic Segmentation**](https://arxiv.org/abs/2202.00432) , (TMM 2022) by *Yang, Guanglei, Fini, Enrico, Xu, Dan, Rota, Paolo, Ding, Mingli, Hao, Tang, Alameda-Pineda, Xavier and Ricci, Elisa* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3468-L3476) +- [**Dark Experience for General Continual Learning: a Strong, Simple Baseline**](https://papers.nips.cc/paper/2020/file/b704ea2c39778f07c617f6b7ce480e9e-Paper.pdf) , (NeurIPS 2020) by *Buzzega, Pietro, Boschini, Matteo, Porrello, Angelo, Abati, Davide and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L288-L298) +- [**Online Continual Learning under Extreme Memory Constraints**](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123730715.pdf) , (ECCV 2020) by *Fini, Enrico, Lathuilière, Stèphane, Sangineto, Enver, Nabi, Moin and Ricci, Elisa* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2515-L2522) ``` Introduces Memory-Constrained Online Continual Learning, a setting where no information can be transferred between tasks, and proposes a distillation-based solution (Batch-level Distillation) ``` -- [**PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning**](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123650086.pdf) , (ECCV 2020) by *Douillard, Arthur, Cord, Matthieu, Ollion, Charles, Robert, Thomas and Valle, Eduardo* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2566-L2573) +- [**PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning**](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123650086.pdf) , (ECCV 2020) by *Douillard, Arthur, Cord, Matthieu, Ollion, Charles, Robert, Thomas and Valle, Eduardo* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2584-L2591) ``` Novel knowledge distillation that trades efficiently rigidity and plasticity to learn large amount of small tasks ``` -- [**Overcoming Catastrophic Forgetting With Unlabeled Data in the Wild**](https://arxiv.org/abs/1903.12648) , (ICCV 2019) by *Lee, Kibok, Lee, Kimin, Shin, Jinwoo and Lee, Honglak* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1057-L1065) +- [**Overcoming Catastrophic Forgetting With Unlabeled Data in the Wild**](https://arxiv.org/abs/1903.12648) , (ICCV 2019) by *Lee, Kibok, Lee, Kimin, Shin, Jinwoo and Lee, Honglak* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1075-L1083) ``` Introducing global distillation loss and balanced finetuning; leveraging unlabeled data in the open world setting (Single-head setting) ``` -- [**Large scale incremental learning**](https://arxiv.org/abs/1905.13260) , (CVPR 2019) by *Wu, Yue, Chen, Yinpeng, Wang, Lijuan, Ye, Yuancheng, Liu, Zicheng, Guo, Yandong and Fu, Yun* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1068-L1076) +- [**Large scale incremental learning**](https://arxiv.org/abs/1905.13260) , (CVPR 2019) by *Wu, Yue, Chen, Yinpeng, Wang, Lijuan, Ye, Yuancheng, Liu, Zicheng, Guo, Yandong and Fu, Yun* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1086-L1094) ``` Introducing bias parameters to the last fully connected layer to resolve the data imbalance issue (Single-head setting) ``` -- **Continual Reinforcement Learning deployed in Real-life using PolicyDistillation and Sim2Real Transfer**, (ICML Workshop 2019) by *Kalifou, René Traoré, Caselles-Dupré, Hugo, Lesort, Timothée, Sun, Te, Diaz-Rodriguez, Natalia and Filliat, David * [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1253-L1259) -- [**Lifelong learning via progressive distillation and retrospection**](https://arxiv.org/abs/1905.13260) , (ECCV 2018) by *Hou, Saihui, Pan, Xinyu, Change Loy, Chen, Wang, Zilei and Lin, Dahua* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1079-L1087) +- **Continual Reinforcement Learning deployed in Real-life using PolicyDistillation and Sim2Real Transfer**, (ICML Workshop 2019) by *Kalifou, René Traoré, Caselles-Dupré, Hugo, Lesort, Timothée, Sun, Te, Diaz-Rodriguez, Natalia and Filliat, David * [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1271-L1277) +- [**Lifelong learning via progressive distillation and retrospection**](https://arxiv.org/abs/1905.13260) , (ECCV 2018) by *Hou, Saihui, Pan, Xinyu, Change Loy, Chen, Wang, Zilei and Lin, Dahua* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1097-L1105) ``` Introducing an expert of the current task in the knowledge distillation method (Multi-head setting) ``` -- [**End-to-end incremental learning**](https://arxiv.org/abs/1807.09536) , (ECCV 2018) by *Castro, Francisco M, Marin-Jimenez, Manuel J, Guil, Nicolas, Schmid, Cordelia and Alahari, Karteek* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1090-L1098) +- [**End-to-end incremental learning**](https://arxiv.org/abs/1807.09536) , (ECCV 2018) by *Castro, Francisco M, Marin-Jimenez, Manuel J, Guil, Nicolas, Schmid, Cordelia and Alahari, Karteek* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1108-L1116) ``` Finetuning the last fully connected layer with a balanced dataset to resolve the data imbalance issue (Single-head setting) ``` -- [**Learning without forgetting**](https://arxiv.org/abs/1606.09282) , (TPAMI 2017) by *Li, Zhizhong and Hoiem, Derek* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L730-L738) +- [**Learning without forgetting**](https://arxiv.org/abs/1606.09282) , (TPAMI 2017) by *Li, Zhizhong and Hoiem, Derek* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L748-L756) ``` Functional regularization through distillation (keeping the output of the updated network on the new data close to the output of the old network on the new data) ``` -- [**icarl: Incremental classifier and representation learning**](https://arxiv.org/abs/1611.07725) , (CVPR 2017) by *Rebuffi, Sylvestre-Alvise, Kolesnikov, Alexander, Sperl, Georg and Lampert, Christoph H* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1101-L1109) +- [**icarl: Incremental classifier and representation learning**](https://arxiv.org/abs/1611.07725) , (CVPR 2017) by *Rebuffi, Sylvestre-Alvise, Kolesnikov, Alexander, Sperl, Georg and Lampert, Christoph H* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1119-L1127) ``` Binary cross-entropy loss for representation learning \& exemplar memory (or coreset) for replay (Single-head setting) ``` ## Rehearsal Methods -- [**On the Effectiveness of Lipschitz-Driven Rehearsal in Continual Learning**](https://arxiv.org/abs/2210.06443) , (NeurIPS 2022) by *Bonicelli, Lorenzo, Boschini, Matteo, Porrello, Angelo, Spampinato, Concetto and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1-L8) -- [**Class-Incremental Continual Learning into the eXtended DER-verse**](https://arxiv.org/abs/2201.00766) , (TPAMI 2022) by *Boschini, Matteo, Bonicelli, Lorenzo, Buzzega, Pietro, Porrello, Angelo and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L10-L19) -- [**Continual semi-supervised learning through contrastive interpolation consistency**](https://arxiv.org/abs/2108.06552) , (PRL 2022) by *Boschini, Matteo, Buzzega, Pietro, Bonicelli, Lorenzo, Porrello, Angelo and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L33-L44) -- [**Transfer without Forgetting**](https://arxiv.org/abs/2206.00388) , (ECCV 2022) by *Boschini, Matteo, Bonicelli, Lorenzo, Porrello, Angelo, Bellitto, Giovanni, Pennisi, Matteo, Palazzo, Simone, Spampinato, Concetto and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L46-L53) -- [**Effects of Auxiliary Knowledge on Continual Learning**](https://arxiv.org/abs/2206.02577) , (ICPR 2022) by *Bellitto, Giovanni, Pennisi, Matteo, Palazzo, Simone, Bonicelli, Lorenzo, Boschini, Matteo, Calderara, Simone and Spampinato, Concetto* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L158-L165) -- [**Rethinking Experience Replay: a Bag of Tricks for Continual Learning**](https://ieeexplore.ieee.org/abstract/document/9412614) , (ICPR 2021) by *Buzzega, Pietro, Boschini, Matteo, Porrello, Angelo and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L257-L268) -- [**Graph-Based Continual Learning**](https://openreview.net/forum?id=HHSEKOnPvaO) , (ICLR 2021) by *Binh Tang and David S. Matteson* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2641-L2648) +- [**MRN: Multiplexed Routing Network for Incremental Multilingual Text Recognition**](https://arxiv.org/abs/2305.14758) , (ICCV 2023) by *Zheng, Tianlun, Chen, Zhineng, Huang, BingChen, Zhang, Wei and Jiang, Yu-Gang* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L19-L26) +- [**On the Effectiveness of Lipschitz-Driven Rehearsal in Continual Learning**](https://arxiv.org/abs/2210.06443) , (NeurIPS 2022) by *Bonicelli, Lorenzo, Boschini, Matteo, Porrello, Angelo, Spampinato, Concetto and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L10-L17) +- [**Class-Incremental Continual Learning into the eXtended DER-verse**](https://arxiv.org/abs/2201.00766) , (TPAMI 2022) by *Boschini, Matteo, Bonicelli, Lorenzo, Buzzega, Pietro, Porrello, Angelo and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L28-L37) +- [**Continual semi-supervised learning through contrastive interpolation consistency**](https://arxiv.org/abs/2108.06552) , (PRL 2022) by *Boschini, Matteo, Buzzega, Pietro, Bonicelli, Lorenzo, Porrello, Angelo and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L51-L62) +- [**Transfer without Forgetting**](https://arxiv.org/abs/2206.00388) , (ECCV 2022) by *Boschini, Matteo, Bonicelli, Lorenzo, Porrello, Angelo, Bellitto, Giovanni, Pennisi, Matteo, Palazzo, Simone, Spampinato, Concetto and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L64-L71) +- [**Effects of Auxiliary Knowledge on Continual Learning**](https://arxiv.org/abs/2206.02577) , (ICPR 2022) by *Bellitto, Giovanni, Pennisi, Matteo, Palazzo, Simone, Bonicelli, Lorenzo, Boschini, Matteo, Calderara, Simone and Spampinato, Concetto* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L176-L183) +- [**Rethinking Experience Replay: a Bag of Tricks for Continual Learning**](https://ieeexplore.ieee.org/abstract/document/9412614) , (ICPR 2021) by *Buzzega, Pietro, Boschini, Matteo, Porrello, Angelo and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L275-L286) +- [**Graph-Based Continual Learning**](https://openreview.net/forum?id=HHSEKOnPvaO) , (ICLR 2021) by *Binh Tang and David S. Matteson* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2659-L2666) ``` Use graphs to link saved samples and improve the memory quality. ``` -- [**Online Class-Incremental Continual Learning with Adversarial Shapley Value**](https://arxiv.org/pdf/2009.00093.pdf) , (2021) by *Dongsub Shim, Zheda Mai, Jihwan Jeong\*, Scott Sanner, Hyunwoo Kim and Jongseong Jang* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2798-L2805) +- [**Online Class-Incremental Continual Learning with Adversarial Shapley Value**](https://arxiv.org/pdf/2009.00093.pdf) , (2021) by *Dongsub Shim, Zheda Mai, Jihwan Jeong\*, Scott Sanner, Hyunwoo Kim and Jongseong Jang* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2816-L2823) ``` Use Shapley Value adversarially to select which samples to relay ``` -- [**Dark Experience for General Continual Learning: a Strong, Simple Baseline**](https://papers.nips.cc/paper/2020/file/b704ea2c39778f07c617f6b7ce480e9e-Paper.pdf) , (NeurIPS 2020) by *Buzzega, Pietro, Boschini, Matteo, Porrello, Angelo, Abati, Davide and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L270-L280) -- **GDumb: A simple approach that questions our progress in continual learning**, (ECCV 2020) by *Prabhu, Ameya, Torr, Philip HS and Dokania, Puneet K* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L282-L290) +- [**Dark Experience for General Continual Learning: a Strong, Simple Baseline**](https://papers.nips.cc/paper/2020/file/b704ea2c39778f07c617f6b7ce480e9e-Paper.pdf) , (NeurIPS 2020) by *Buzzega, Pietro, Boschini, Matteo, Porrello, Angelo, Abati, Davide and Calderara, Simone* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L288-L298) +- **GDumb: A simple approach that questions our progress in continual learning**, (ECCV 2020) by *Prabhu, Ameya, Torr, Philip HS and Dokania, Puneet K* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L300-L308) ``` introduces a super simple methods that outperforms almost all methods in all of the CL benchmarks. We need new better benchamrks ``` -- [**Continual Learning: Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes**](https://arxiv.org/abs/2007.00487) , (2020) by *Timothée Lesort* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L337-L346) -- [**Imbalanced Continual Learning with Partitioning Reservoir Sampling**](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123580409.pdf) , (ECCV 2020) by *Kim, Chris Dongjoo, Jeong, Jinseo and Kim, Gunhee* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2470-L2477) -- [**PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning**](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123650086.pdf) , (ECCV 2020) by *Douillard, Arthur, Cord, Matthieu, Ollion, Charles, Robert, Thomas and Valle, Eduardo* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2566-L2573) +- [**Continual Learning: Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes**](https://arxiv.org/abs/2007.00487) , (2020) by *Timothée Lesort* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L355-L364) +- [**Imbalanced Continual Learning with Partitioning Reservoir Sampling**](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123580409.pdf) , (ECCV 2020) by *Kim, Chris Dongjoo, Jeong, Jinseo and Kim, Gunhee* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2488-L2495) +- [**PODNet: Pooled Outputs Distillation for Small-Tasks Incremental Learning**](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123650086.pdf) , (ECCV 2020) by *Douillard, Arthur, Cord, Matthieu, Ollion, Charles, Robert, Thomas and Valle, Eduardo* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2584-L2591) ``` Novel knowledge distillation that trades efficiently rigidity and plasticity to learn large amount of small tasks ``` - [**{REMIND Your Neural Network to Prevent Catastrophic Forgetting}**](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123650681.pdf) , (ECCV 2020) by *Hayes, Tyler L., Kafle, Kushal, Shrestha, Robik and -Acharya, Manoj and Kanan, Christopher* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2585-L2593) -- [**Efficient Lifelong Learning with A-GEM**](https://arxiv.org/abs/1812.00420) , (ICLR 2019) by *Chaudhry, Arslan, Ranzato, Marc’Aurelio, Rohrbach, Marcus and Elhoseiny, Mohamed* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L445-L452) +Acharya, Manoj and Kanan, Christopher* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2603-L2611) +- [**Efficient Lifelong Learning with A-GEM**](https://arxiv.org/abs/1812.00420) , (ICLR 2019) by *Chaudhry, Arslan, Ranzato, Marc’Aurelio, Rohrbach, Marcus and Elhoseiny, Mohamed* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L463-L470) ``` More efficient GEM; Introduces online continual learning ``` -- [**Orthogonal Gradient Descent for Continual Learning**](https://arxiv.org/abs/1910.07104) , (2019) by *Mehrdad Farajtabar, Navid Azizan, Alex Mott and Ang Li* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L799-L808) +- [**Orthogonal Gradient Descent for Continual Learning**](https://arxiv.org/abs/1910.07104) , (2019) by *Mehrdad Farajtabar, Navid Azizan, Alex Mott and Ang Li* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L817-L826) ``` projecting the gradients from new tasks onto a subspace in which the neural network output on previous task does not change and the projected gradient is still in a useful direction for learning the new task ``` -- [**Gradient based sample selection for online continual learning**](http://papers.nips.cc/paper/9354-gradient-based-sample-selection-for-online-continual-learning.pdf) , (NeurIPS 2019) by *Aljundi, Rahaf, Lin, Min, Goujaud, Baptiste and Bengio, Yoshua* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L812-L822) +- [**Gradient based sample selection for online continual learning**](http://papers.nips.cc/paper/9354-gradient-based-sample-selection-for-online-continual-learning.pdf) , (NeurIPS 2019) by *Aljundi, Rahaf, Lin, Min, Goujaud, Baptiste and Bengio, Yoshua* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L830-L840) ``` sample selection as a constraint reduction problem based on the constrained optimization view of continual learning ``` - [**Online Continual Learning with Maximal Interfered Retrieval**](http://papers.nips.cc/paper/9357-online-continual-learning-with-maximal-interfered-retrieval.pdf) , (NeurIPS 2019) by *Aljundi, Rahaf and -, Lucas, Belilovsky, Eugene, Caccia, Massimo, Lin, Min, Charlin, Laurent and Tuytelaars, Tinne* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L826-L837) +, Lucas, Belilovsky, Eugene, Caccia, Massimo, Lin, Min, Charlin, Laurent and Tuytelaars, Tinne* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L844-L855) ``` Controlled sampling of memories for replay to automatically rehearse on tasks currently undergoing the most forgetting ``` -- [**Online Learned Continual Compression with Adaptative Quantization Module**](https://arxiv.org/abs/1911.08019) , (arXiv 2019) by *Caccia, Lucas, Belilovsky, Eugene, Caccia, Massimo and Pineau, Joelle* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L841-L848) +- [**Online Learned Continual Compression with Adaptative Quantization Module**](https://arxiv.org/abs/1911.08019) , (arXiv 2019) by *Caccia, Lucas, Belilovsky, Eugene, Caccia, Massimo and Pineau, Joelle* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L859-L866) ``` Uses stacks of VQ-VAE modules to progressively compress the data stream, enabling better rehearsal ``` -- [**Large scale incremental learning**](https://arxiv.org/abs/1905.13260) , (CVPR 2019) by *Wu, Yue, Chen, Yinpeng, Wang, Lijuan, Ye, Yuancheng, Liu, Zicheng, Guo, Yandong and Fu, Yun* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1068-L1076) +- [**Large scale incremental learning**](https://arxiv.org/abs/1905.13260) , (CVPR 2019) by *Wu, Yue, Chen, Yinpeng, Wang, Lijuan, Ye, Yuancheng, Liu, Zicheng, Guo, Yandong and Fu, Yun* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1086-L1094) ``` Introducing bias parameters to the last fully connected layer to resolve the data imbalance issue (Single-head setting) ``` -- **Learning a Unified Classifier Incrementally via Rebalancing**, (CVPR 2019) by *Hou, Saihui, Pan, Xinyu, Loy, Chen Change, Wang, Zilei and Lin, Dahua* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1113-L1120) -- **Continual Reinforcement Learning deployed in Real-life using PolicyDistillation and Sim2Real Transfer**, (ICML Workshop 2019) by *Kalifou, René Traoré, Caselles-Dupré, Hugo, Lesort, Timothée, Sun, Te, Diaz-Rodriguez, Natalia and Filliat, David * [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1253-L1259) -- [**Experience replay for continual learning**](https://arxiv.org/abs/1811.11682) , (NeurIPS 2019) by *Rolnick, David, Ahuja, Arun, Schwarz, Jonathan, Lillicrap, Timothy and Wayne, Gregory* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1461-L1469) -- [**Gradient Episodic Memory for Continual Learning**](http://papers.nips.cc/paper/7225-gradient-episodic-memory-for-continual-learning.pdf) , (NeurIPS 2017) by *Lopez-Paz, David and Ranzato, Marc-Aurelio* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L467-L477) +- **Learning a Unified Classifier Incrementally via Rebalancing**, (CVPR 2019) by *Hou, Saihui, Pan, Xinyu, Loy, Chen Change, Wang, Zilei and Lin, Dahua* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1131-L1138) +- **Continual Reinforcement Learning deployed in Real-life using PolicyDistillation and Sim2Real Transfer**, (ICML Workshop 2019) by *Kalifou, René Traoré, Caselles-Dupré, Hugo, Lesort, Timothée, Sun, Te, Diaz-Rodriguez, Natalia and Filliat, David * [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1271-L1277) +- [**Experience replay for continual learning**](https://arxiv.org/abs/1811.11682) , (NeurIPS 2019) by *Rolnick, David, Ahuja, Arun, Schwarz, Jonathan, Lillicrap, Timothy and Wayne, Gregory* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1479-L1487) +- [**Gradient Episodic Memory for Continual Learning**](http://papers.nips.cc/paper/7225-gradient-episodic-memory-for-continual-learning.pdf) , (NeurIPS 2017) by *Lopez-Paz, David and Ranzato, Marc-Aurelio* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L485-L495) ``` A model that alliviates CF via constrained optimization ``` -- [**icarl: Incremental classifier and representation learning**](https://arxiv.org/abs/1611.07725) , (CVPR 2017) by *Rebuffi, Sylvestre-Alvise, Kolesnikov, Alexander, Sperl, Georg and Lampert, Christoph H* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1101-L1109) +- [**icarl: Incremental classifier and representation learning**](https://arxiv.org/abs/1611.07725) , (CVPR 2017) by *Rebuffi, Sylvestre-Alvise, Kolesnikov, Alexander, Sperl, Georg and Lampert, Christoph H* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1119-L1127) ``` Binary cross-entropy loss for representation learning \& exemplar memory (or coreset) for replay (Single-head setting) ``` -- [**Catastrophic Forgetting, Rehearsal and Pseudorehearsal**](https://doi.org/10.1080/09540099550039318) , (1995) by * Anthony Robins * [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2075-L2088) +- [**Catastrophic Forgetting, Rehearsal and Pseudorehearsal**](https://doi.org/10.1080/09540099550039318) , (1995) by * Anthony Robins * [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2093-L2106) ## Generative Replay Methods -- [**Continual Learning: Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes**](https://arxiv.org/abs/2007.00487) , (2020) by *Timothée Lesort* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L337-L346) -- [**Brain-Like Replay For Continual Learning With Artificial Neural Networks**](https://baicsworkshop.github.io/pdf/BAICS_8.pdf) , (2020) by *van de Ven, Gido M, Siegelmann, Hava T and Tolias, Andreas S* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L415-L421) -- [**Learning to remember: A synaptic plasticity driven framework for continual learning**](https://openaccess.thecvf.com/content_CVPR_2019/html/Ostapenko_Learning_to_Remember_A_Synaptic_Plasticity_Driven_Framework_for_Continual_CVPR_2019_paper.html) , (CVPR 2019) by *Ostapenko, Oleksiy, Puscas, Mihai, Klein, Tassilo, Jahnichen, Patrick and Nabi, Moin* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L305-L313) +- [**Continual Learning: Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes**](https://arxiv.org/abs/2007.00487) , (2020) by *Timothée Lesort* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L355-L364) +- [**Brain-Like Replay For Continual Learning With Artificial Neural Networks**](https://baicsworkshop.github.io/pdf/BAICS_8.pdf) , (2020) by *van de Ven, Gido M, Siegelmann, Hava T and Tolias, Andreas S* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L433-L439) +- [**Learning to remember: A synaptic plasticity driven framework for continual learning**](https://openaccess.thecvf.com/content_CVPR_2019/html/Ostapenko_Learning_to_Remember_A_Synaptic_Plasticity_Driven_Framework_for_Continual_CVPR_2019_paper.html) , (CVPR 2019) by *Ostapenko, Oleksiy, Puscas, Mihai, Klein, Tassilo, Jahnichen, Patrick and Nabi, Moin* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L323-L331) ``` introdudes Dynamic generative memory (DGM) which relies on conditional generative adversarial networks with learnable connection plasticity realized with neural masking ``` -- [**Generative Models from the perspective of Continual Learning**](https://hal.archives-ouvertes.fr/hal-01951954) , (IJCNN 2019) by *Lesort, Timothée, Caselles-Dupré, Hugo, Garcia-Ortiz, Michael, Goudou, Jean-Fran{\c c}ois and Filliat, David* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L954-L966) +- [**Generative Models from the perspective of Continual Learning**](https://hal.archives-ouvertes.fr/hal-01951954) , (IJCNN 2019) by *Lesort, Timothée, Caselles-Dupré, Hugo, Garcia-Ortiz, Michael, Goudou, Jean-Fran{\c c}ois and Filliat, David* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L972-L984) ``` Extensive evaluation of CL methods for generative modeling ``` -- [**Closed-loop Memory GAN for Continual Learning**](http://dl.acm.org/citation.cfm?id=3367471.3367504) , (IJCAI 2019) by *Rios, Amanda and Itti, Laurent* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1261-L1275) -- [**Marginal replay vs conditional replay for continual learning**](https://arxiv.org/abs/1810.12069) , (ICANN 2019) by *Lesort, Timothée, Gepperth, Alexander, Stoian, Andrei and Filliat, David* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1406-L1415) +- [**Closed-loop Memory GAN for Continual Learning**](http://dl.acm.org/citation.cfm?id=3367471.3367504) , (IJCAI 2019) by *Rios, Amanda and Itti, Laurent* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1279-L1293) +- [**Marginal replay vs conditional replay for continual learning**](https://arxiv.org/abs/1810.12069) , (ICANN 2019) by *Lesort, Timothée, Gepperth, Alexander, Stoian, Andrei and Filliat, David* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1424-L1433) ``` Extensive evaluation of generative replay methods ``` -- [**Generative replay with feedback connections as a general strategy for continual learning**](https://arxiv.org/abs/1809.10635) , (2018) by *Michiel van der Ven and Andreas S. Tolias* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L852-L860) +- [**Generative replay with feedback connections as a general strategy for continual learning**](https://arxiv.org/abs/1809.10635) , (2018) by *Michiel van der Ven and Andreas S. Tolias* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L870-L878) ``` smarter Generative Replay ``` -- [**Continual learning with deep generative replay**](https://arxiv.org/abs/1705.08690) , (NeurIPS 2017) by *Shin, Hanul, Lee, Jung Kwon, Kim, Jaehong and Kim, Jiwon* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L481-L489) +- [**Continual learning with deep generative replay**](https://arxiv.org/abs/1705.08690) , (NeurIPS 2017) by *Shin, Hanul, Lee, Jung Kwon, Kim, Jaehong and Kim, Jiwon* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L499-L507) ``` Introduces generative replay ``` ## Dynamic Architectures or Routing Methods -- [**Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic Environments**](https://www.frontiersin.org/articles/10.3389/fnbot.2022.846219/full) , (2022) by *Iyer, Abhiram, Grewal, Karan, Velu, Akash, Souza, Lucas Oliveira, Forest, Jeremy and Ahmad, Subutai* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L77-L86) +- [**Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic Environments**](https://www.frontiersin.org/articles/10.3389/fnbot.2022.846219/full) , (2022) by *Iyer, Abhiram, Grewal, Karan, Velu, Akash, Souza, Lucas Oliveira, Forest, Jeremy and Ahmad, Subutai* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L95-L104) ``` bio-inspired method which dynamically restrict and route information in a context-specific manner ``` -- [**DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion**](https://arxiv.org/abs/2111.11326) , (arXiv 2021) by *Douillard, Arthur, Ram{\'e}, Alexandre, Couairon, Guillaume and Cord, Matthieu* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3313-L3320) -- [**Supermasks in superposition**](https://arxiv.org/abs/2006.14769) , (2020) by *Wortsman, Mitchell, Ramanujan, Vivek, Liu, Rosanne, Kembhavi, Aniruddha, Rastegari, Mohammad, Yosinski, Jason and Farhadi, Ali* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L65-L74) +- [**DyTox: Transformers for Continual Learning with DYnamic TOken eXpansion**](https://arxiv.org/abs/2111.11326) , (arXiv 2021) by *Douillard, Arthur, Ram{\'e}, Alexandre, Couairon, Guillaume and Cord, Matthieu* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3331-L3338) +- [**Supermasks in superposition**](https://arxiv.org/abs/2006.14769) , (2020) by *Wortsman, Mitchell, Ramanujan, Vivek, Liu, Rosanne, Kembhavi, Aniruddha, Rastegari, Mohammad, Yosinski, Jason and Farhadi, Ali* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L83-L92) ``` a binary mask over the network is inferred based on the input, and only the masked part of the network is used to train/infer ``` - [**ORACLE: Order Robust Adaptive Continual Learning**](http://arxiv.org/abs/1902.09432) , (2019) by *Jaehong Yoon and Saehoon Kim and Eunho Yang and -Sung Ju Hwang* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L592-L608) +Sung Ju Hwang* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L610-L626) - [**Learn to Grow: {A} Continual Structure Learning Framework for Overcoming Catastrophic Forgetting**](http://arxiv.org/abs/1904.00310) , (2019) by *Xilai Li and Yingbo Zhou and Tianfu Wu and Richard Socher and -Caiming Xiong* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2206-L2224) -- [**Alleviating catastrophic forgetting using context-dependent gating and synaptic stabilization**](https://www.pnas.org/doi/pdf/10.1073/pnas.1803839115) , (2018) by *Masse, Nicolas Y, Grant, Gregory D and Freedman, David J* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L90-L101) +Caiming Xiong* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2224-L2242) +- [**Alleviating catastrophic forgetting using context-dependent gating and synaptic stabilization**](https://www.pnas.org/doi/pdf/10.1073/pnas.1803839115) , (2018) by *Masse, Nicolas Y, Grant, Gregory D and Freedman, David J* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L108-L119) ``` a network trained to do CL where select subnetworks are used to learn each task; these subnetworks are chosen a priori ``` -- [**Incremental Learning through Deep Adaptation**](https://openreview.net/forum?id=ryj0790hb) , (2018) by *Amir Rosenfeld and John K. Tsotsos* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L753-L759) -- **Packnet: Adding multiple tasks to a single network by iterative pruning**, (CVPR 2018) by *Mallya, Arun and Lazebnik, Svetlana* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1123-L1130) -- **Piggyback: Adapting a single network to multiple tasks by learning to mask weights**, (ECCV 2018) by *Mallya, Arun, Davis, Dillon and Lazebnik, Svetlana* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1132-L1139) -- [**Continual Learning in Practice**](https://arxiv.org/abs/1903.05202) , (NeurIPS Workshop 2018) by *Diethe, Tom, Borchert, Tom, Thereska, Eno, Pigem, Borja de Balle and Lawrence, Neil* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2327-L2334) +- [**Incremental Learning through Deep Adaptation**](https://openreview.net/forum?id=ryj0790hb) , (2018) by *Amir Rosenfeld and John K. Tsotsos* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L771-L777) +- **Packnet: Adding multiple tasks to a single network by iterative pruning**, (CVPR 2018) by *Mallya, Arun and Lazebnik, Svetlana* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1141-L1148) +- **Piggyback: Adapting a single network to multiple tasks by learning to mask weights**, (ECCV 2018) by *Mallya, Arun, Davis, Dillon and Lazebnik, Svetlana* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1150-L1157) +- [**Continual Learning in Practice**](https://arxiv.org/abs/1903.05202) , (NeurIPS Workshop 2018) by *Diethe, Tom, Borchert, Tom, Thereska, Eno, Pigem, Borja de Balle and Lawrence, Neil* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2345-L2352) ``` Proposes a reference architecture for a continual learning system ``` -- **Growing a brain: Fine-tuning by increasing model capacity**, (CVPR 2017) by *Wang, Yu-Xiong, Ramanan, Deva and Hebert, Martial* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1141-L1148) +- **Growing a brain: Fine-tuning by increasing model capacity**, (CVPR 2017) by *Wang, Yu-Xiong, Ramanan, Deva and Hebert, Martial* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1159-L1166) - [**PathNet: Evolution Channels Gradient Descent in Super Neural Networks**](http://arxiv.org/abs/1701.08734) , (2017) by *Chrisantha Fernando and Dylan Banarse and Charles Blundell and @@ -279,75 +281,75 @@ Yori Zwols and David Ha and Andrei A. Rusu and Alexander Pritzel and -Daan Wierstra* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1796-L1816) -- **Lifelong learning with dynamically expandable networks**, (arXiv 2017) by *Yoon, Jaehong, Yang, Eunho, Lee, Jeongtae and Hwang, Sung Ju* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2066-L2072) +Daan Wierstra* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1814-L1834) +- **Lifelong learning with dynamically expandable networks**, (arXiv 2017) by *Yoon, Jaehong, Yang, Eunho, Lee, Jeongtae and Hwang, Sung Ju* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2084-L2090) - [**Progressive Neural Networks**](https://arxiv.org/abs/1606.04671) , (2016) by *Rusu, A.~A., Rabinowitz, N.~C., Desjardins, G. and Soyer, H., Kirkpatrick, J., Kavukcuoglu, K. and -Pascanu, R. and Hadsell, R.* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L761-L776) +Pascanu, R. and Hadsell, R.* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L779-L794) ``` Each task have a specific model connected to the previous ones ``` ## Hybrid Methods -- [**Continual learning with hypernetworks**](https://openreview.net/forum?id=SJgwNerKvB) , (ICLR 2020) by *Johannes von Oswald, Christian Henning, João Sacramento and Benjamin F. Grewe* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1005-L1012) +- [**Continual learning with hypernetworks**](https://openreview.net/forum?id=SJgwNerKvB) , (ICLR 2020) by *Johannes von Oswald, Christian Henning, João Sacramento and Benjamin F. Grewe* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1023-L1030) ``` Learning task-conditioned hypernetworks for continual learning as well as task embeddings; hypernetwors offers good model compression. ``` -- [**Compacting, Picking and Growing for Unforgetting Continual Learning**](https://arxiv.org/abs/1910.06562) , (NeurIPS 2019) by *Hung, Ching-Yi, Tu, Cheng-Hao, Wu, Cheng-En, Chen, Chien-Hung, Chan, Yi-Ming and Chen, Chu-Song* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L534-L542) +- [**Compacting, Picking and Growing for Unforgetting Continual Learning**](https://arxiv.org/abs/1910.06562) , (NeurIPS 2019) by *Hung, Ching-Yi, Tu, Cheng-Hao, Wu, Cheng-En, Chen, Chien-Hung, Chan, Yi-Ming and Chen, Chu-Song* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L552-L560) ``` Approach leverages the principles of deep model compression, critical weights selection, and progressive networks expansion. All enforced in an iterative manner ``` -- [**A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning**](https://arxiv.org/pdf/2001.00689.pdf) , (ICLR 2019) by *Lee, Soochan, Ha, Junsoo, Zhang, Dongsu and Kim, Gunhee* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1540-L1547) +- [**A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning**](https://arxiv.org/pdf/2001.00689.pdf) , (ICLR 2019) by *Lee, Soochan, Ha, Junsoo, Zhang, Dongsu and Kim, Gunhee* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1558-L1565) ``` This paper introduces expansion-based approach for task-free continual learning ``` ## Continual Few-Shot Learning -- [**Learning where to learn: Gradient sparsity in meta and continual learning**](https://proceedings.neurips.cc/paper/2021/hash/2a10665525774fa2501c2c8c4985ce61-Abstract.html) , (2021) by *Von Oswald, Johannes, Zhao, Dominic, Kobayashi, Seijin, Schug, Simon, Caccia, Massimo, Zucchet, Nicolas and Sacramento, Jo{\~a}o* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L247-L255) -- [**Wandering Within a World: Online Contextualized Few-Shot Learning**](https://arxiv.org/abs/2007.04546) , (2020) by *Mengye Ren, Michael L. Iuzzolino, Michael C. Mozer and Richard S. Zemel* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L325-L333) +- [**Learning where to learn: Gradient sparsity in meta and continual learning**](https://proceedings.neurips.cc/paper/2021/hash/2a10665525774fa2501c2c8c4985ce61-Abstract.html) , (2021) by *Von Oswald, Johannes, Zhao, Dominic, Kobayashi, Seijin, Schug, Simon, Caccia, Massimo, Zucchet, Nicolas and Sacramento, Jo{\~a}o* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L265-L273) +- [**Wandering Within a World: Online Contextualized Few-Shot Learning**](https://arxiv.org/abs/2007.04546) , (2020) by *Mengye Ren, Michael L. Iuzzolino, Michael C. Mozer and Richard S. Zemel* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L343-L351) ``` proposes a new continual few-shot setting where spacial and temporal context can be leveraged to and unseen classes need to be predicted ``` -- [**Defining Benchmarks for Continual Few-Shot Learning**](https://arxiv.org/abs/2004.11967) , (arXiv 2020) by *Antoniou, Antreas, Patacchiola, Massimiliano, Ochal, Mateusz and Storkey, Amos* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L367-L374) +- [**Defining Benchmarks for Continual Few-Shot Learning**](https://arxiv.org/abs/2004.11967) , (arXiv 2020) by *Antoniou, Antreas, Patacchiola, Massimiliano, Ochal, Mateusz and Storkey, Amos* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L385-L392) ``` (title is a good enough summary) ``` -- [**Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning**](https://arxiv.org/abs/2003.05856) , (2020) by *Caccia, Massimo, Rodriguez, Pau, Ostapenko, Oleksiy, Normandin, Fabrice, Lin, Min, Caccia, Lucas, Laradji, Issam, Rish, Irina, Lacoste, Alexandre, Vazquez, David and Charlin, Laurent* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1473-L1480) +- [**Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning**](https://arxiv.org/abs/2003.05856) , (2020) by *Caccia, Massimo, Rodriguez, Pau, Ostapenko, Oleksiy, Normandin, Fabrice, Lin, Min, Caccia, Lucas, Laradji, Issam, Rish, Irina, Lacoste, Alexandre, Vazquez, David and Charlin, Laurent* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1491-L1498) ``` Proposes a new approach to CL evaluation more aligned with real-life applications, bringing CL closer to Online Learning and Open-World learning ``` -- [**Learning from the Past: Continual Meta-Learning via Bayesian Graph Modeling**](https://arxiv.org/abs/1911.04695) , (2019) by *Yadan Luo, Zi Huang, Zheng Zhang, Ziwei Wang, Mahsa Baktashmotlagh and Yang Yang* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L876-L885) -- [**Online Meta-Learning**](http://proceedings.mlr.press/v97/finn19a.html) , (ICML 2019) by *Finn, Chelsea, Rajeswaran, Aravind, Kakade, Sham and Levine, Sergey* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L898-L913) +- [**Learning from the Past: Continual Meta-Learning via Bayesian Graph Modeling**](https://arxiv.org/abs/1911.04695) , (2019) by *Yadan Luo, Zi Huang, Zheng Zhang, Ziwei Wang, Mahsa Baktashmotlagh and Yang Yang* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L894-L903) +- [**Online Meta-Learning**](http://proceedings.mlr.press/v97/finn19a.html) , (ICML 2019) by *Finn, Chelsea, Rajeswaran, Aravind, Kakade, Sham and Levine, Sergey* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L916-L931) ``` defines Online Meta-learning; propsoses Follow the Meta Leader (FTML) (~ Online MAML) ``` -- [**Reconciling meta-learning and continual learning with online mixtures of tasks**](http://papers.nips.cc/paper/9112-reconciling-meta-learning-and-continual-learning-with-online-mixtures-of-tasks.pdf) , (NeurIPS 2019) by *Jerfel, Ghassen, Grant, Erin, Griffiths, Tom and Heller, Katherine A* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L917-L927) +- [**Reconciling meta-learning and continual learning with online mixtures of tasks**](http://papers.nips.cc/paper/9112-reconciling-meta-learning-and-continual-learning-with-online-mixtures-of-tasks.pdf) , (NeurIPS 2019) by *Jerfel, Ghassen, Grant, Erin, Griffiths, Tom and Heller, Katherine A* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L935-L945) ``` Meta-learns a tasks structure; continual adaptation via non-parametric prior ``` -- [**Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL**](https://openreview.net/forum?id=HyxAfnA5tm) , (ICLR 2019) by *Anusha Nagabandi, Chelsea Finn and Sergey Levine* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L932-L939) +- [**Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL**](https://openreview.net/forum?id=HyxAfnA5tm) , (ICLR 2019) by *Anusha Nagabandi, Chelsea Finn and Sergey Levine* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L950-L957) ``` Formulates an online learning procedure that uses SGD to update model parameters, and an EM with a Chinese restaurant process prior to develop and maintain a mixture of models to handle non-stationary task distribution ``` -- [**Task Agnostic Continual Learning via Meta Learning**](https://arxiv.org/abs/1906.05201) , (2019) by *Xu He, Jakub Sygnowski, Alexandre Galashov, Andrei A. Rusu, Yee Whye Teh and Razvan Pascanu* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1028-L1036) +- [**Task Agnostic Continual Learning via Meta Learning**](https://arxiv.org/abs/1906.05201) , (2019) by *Xu He, Jakub Sygnowski, Alexandre Galashov, Andrei A. Rusu, Yee Whye Teh and Razvan Pascanu* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1046-L1054) ``` Introduces What \& How framework; enables Task Agnostic CL with meta learned task inference ``` ## Meta-Continual Learning -- [**Learning where to learn: Gradient sparsity in meta and continual learning**](https://proceedings.neurips.cc/paper/2021/hash/2a10665525774fa2501c2c8c4985ce61-Abstract.html) , (2021) by *Von Oswald, Johannes, Zhao, Dominic, Kobayashi, Seijin, Schug, Simon, Caccia, Massimo, Zucchet, Nicolas and Sacramento, Jo{\~a}o* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L247-L255) -- [**La-MAML: Look-ahead Meta Learning for Continual Learning**](https://arxiv.org/abs/2007.13904) , (2020) by *Gunshi Gupta, Karmesh Yadav and Liam Paull* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L316-L322) +- [**Learning where to learn: Gradient sparsity in meta and continual learning**](https://proceedings.neurips.cc/paper/2021/hash/2a10665525774fa2501c2c8c4985ce61-Abstract.html) , (2021) by *Von Oswald, Johannes, Zhao, Dominic, Kobayashi, Seijin, Schug, Simon, Caccia, Massimo, Zucchet, Nicolas and Sacramento, Jo{\~a}o* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L265-L273) +- [**La-MAML: Look-ahead Meta Learning for Continual Learning**](https://arxiv.org/abs/2007.13904) , (2020) by *Gunshi Gupta, Karmesh Yadav and Liam Paull* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L334-L340) ``` Proposes an online replay-based meta-continual learning algorithm with learning-rate modulation to mitigate catastrophic forgetting ``` -- [**Learning to Continually Learn**](https://arxiv.org/abs/2002.09571) , (arXiv 2020) by *Beaulieu, Shawn, Frati, Lapo, Miconi, Thomas, Lehman, Joel, Stanley, Kenneth O, Clune, Jeff and Cheney, Nick* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1431-L1438) +- [**Learning to Continually Learn**](https://arxiv.org/abs/2002.09571) , (arXiv 2020) by *Beaulieu, Shawn, Frati, Lapo, Miconi, Thomas, Lehman, Joel, Stanley, Kenneth O, Clune, Jeff and Cheney, Nick* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1449-L1456) ``` Follow-up of OML. Meta-learns an activation-gating function instead. ``` -- [**Meta-Learning Representations for Continual Learning**](http://papers.nips.cc/paper/8458-meta-learning-representations-for-continual-learning.pdf) , (NeurIPS 2019) by *Javed, Khurram and White, Martha* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L863-L873) +- [**Meta-Learning Representations for Continual Learning**](http://papers.nips.cc/paper/8458-meta-learning-representations-for-continual-learning.pdf) , (NeurIPS 2019) by *Javed, Khurram and White, Martha* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L881-L891) ``` Introduces Learns how to continually learn (OML) i.e. learns how to do online updates without forgetting. ``` -- [**Meta-learnt priors slow down catastrophic forgetting in neural networks**](https://arxiv.org/pdf/1909.04170.pdf) , (arXiv 2019) by *Spigler, Giacomo* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1441-L1448) +- [**Meta-learnt priors slow down catastrophic forgetting in neural networks**](https://arxiv.org/pdf/1909.04170.pdf) , (arXiv 2019) by *Spigler, Giacomo* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1459-L1466) ``` Learning MAML in a Meta continual learning way slows down forgetting ``` -- [**Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference**](https://openreview.net/forum?id=B1gTShAct7) , (ICLR 2019) by *Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu and and Gerald Tesauro* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1452-L1459) +- [**Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference**](https://openreview.net/forum?id=B1gTShAct7) , (ICLR 2019) by *Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu and and Gerald Tesauro* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1470-L1477) ## Lifelong Reinforcement Learning -- [**A Study of Continual Learning Methods for Q-Learning**](https://arxiv.org/abs/2206.03934) , (arXiv 2022) by *Bagus, Benedikt and Gepperth, Alexander* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L55-L62) +- [**A Study of Continual Learning Methods for Q-Learning**](https://arxiv.org/abs/2206.03934) , (arXiv 2022) by *Bagus, Benedikt and Gepperth, Alexander* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L73-L80) ``` Studies Q-Learning methods in CRL environments. When there's no task interference, (A-)GEM can outperform Experience Replay ``` -- [**Co{MPS}: Continual Meta Policy Search**](https://openreview.net/forum?id=PVJ6j87gOHz) , (ICLR 2022) by *Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn and Sergey Levine* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L126-L133) +- [**Co{MPS}: Continual Meta Policy Search**](https://openreview.net/forum?id=PVJ6j87gOHz) , (ICLR 2022) by *Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn and Sergey Levine* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L144-L151) ``` Co{MPS} is a novel meta-policy search algorithm for task-agnostic continual RL ``` -- [**Task-Agnostic Continual Reinforcement Learning: In Praise of a Simple Baseline**](https://arxiv.org/abs/2205.14495) , (arXiv 2022) by *Caccia, Massimo, Mueller, Jonas, Kim, Taesup, Charlin, Laurent and Fakoor, Rasool* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L136-L143) +- [**Task-Agnostic Continual Reinforcement Learning: In Praise of a Simple Baseline**](https://arxiv.org/abs/2205.14495) , (arXiv 2022) by *Caccia, Massimo, Mueller, Jonas, Kim, Taesup, Charlin, Laurent and Fakoor, Rasool* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L154-L161) ``` combines replay and an RNN to set a simple baseline for TACRL: shows that the baselines matches and surpasses previously thought upper bounds ``` -- [**Modular Lifelong Reinforcement Learning via Neural Composition**](https://openreview.net/forum?id=5XmLzdslFNN) , (ICLR 2022) by *Jorge A Mendez, Harm van Seijen and ERIC EATON* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L180-L187) -- [**Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning**](https://arxiv.org/abs/2207.05742) , (2022) by *Steinparz, Christian, Schmied, Thomas, Paischer, Fabian, Dinu, Marius-Constantin, Patil, Vihang, Bitto-Nemling, Angela, Eghbal-zadeh, Hamid and Hochreiter, Sepp* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3460-L3467) +- [**Modular Lifelong Reinforcement Learning via Neural Composition**](https://openreview.net/forum?id=5XmLzdslFNN) , (ICLR 2022) by *Jorge A Mendez, Harm van Seijen and ERIC EATON* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L198-L205) +- [**Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning**](https://arxiv.org/abs/2207.05742) , (2022) by *Steinparz, Christian, Schmied, Thomas, Paischer, Fabian, Dinu, Marius-Constantin, Patil, Vihang, Bitto-Nemling, Angela, Eghbal-zadeh, Hamid and Hochreiter, Sepp* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3478-L3485) ``` Detects changes and explores when and where they happen to recover from non-stationarity. ``` -- [**Same State, Different Task: Continual Reinforcement Learning without Interference**](https://arxiv.org/abs/2106.02940) , (2021) by *Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren and Stephen J. Roberts* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L114-L122) +- [**Same State, Different Task: Continual Reinforcement Learning without Interference**](https://arxiv.org/abs/2106.02940) , (2021) by *Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren and Stephen J. Roberts* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L132-L140) ``` learns multiple policies and cast policy-retrieval as a multi-arm bandit problem ``` -- [**CoMPS: Continual Meta Policy Search**](https://arxiv.org/abs/2112.04467) , (2021) by *Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn and Sergey Levine* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L189-L198) -- [**Reset-Free Lifelong Learning with Skill-Space Planning**](https://openreview.net/forum?id=HIGSa_3kOx3) , (ICLR 2021) by *Kevin Lu, Aditya Grover, Pieter Abbeel and Igor Mordatch* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2725-L2732) -- [**Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes**](https://arxiv.org/abs/2006.11441) , (2020) by *Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen and Ding Zhao* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L146-L154) +- [**CoMPS: Continual Meta Policy Search**](https://arxiv.org/abs/2112.04467) , (2021) by *Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn and Sergey Levine* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L207-L216) +- [**Reset-Free Lifelong Learning with Skill-Space Planning**](https://openreview.net/forum?id=HIGSa_3kOx3) , (ICLR 2021) by *Kevin Lu, Aditya Grover, Pieter Abbeel and Igor Mordatch* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2743-L2750) +- [**Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes**](https://arxiv.org/abs/2006.11441) , (2020) by *Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen and Ding Zhao* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L164-L172) ``` uses an infinite mixture of Gaussian Processes to learn a task-agnostic policy ``` -- [**Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting**](https://arxiv.org/abs/2007.07011) , (2020) by *Jorge A. Mendez, Boyu Wang and Eric Eaton* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L200-L210) -- **Towards Continual Reinforcement Learning: A Review and Perspectives**, (2020) by *Khimya Khetarpal, Matthew Riemer, Irina Rish and Doina Precup* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L293-L301) +- [**Lifelong Policy Gradient Learning of Factored Policies for Faster Training Without Forgetting**](https://arxiv.org/abs/2007.07011) , (2020) by *Jorge A. Mendez, Boyu Wang and Eric Eaton* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L218-L228) +- **Towards Continual Reinforcement Learning: A Review and Perspectives**, (2020) by *Khimya Khetarpal, Matthew Riemer, Irina Rish and Doina Precup* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L311-L319) ``` A review on continual reinforcement learning ``` -- [**Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges**](http://www.sciencedirect.com/science/article/pii/S1566253519307377) , (Information Fusion 2020) by *Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat and Natalia Díaz-Rodríguez* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1321-L1332) -- [**Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL**](https://openreview.net/forum?id=HyxAfnA5tm) , (ICLR 2019) by *Anusha Nagabandi, Chelsea Finn and Sergey Levine* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L932-L939) +- [**Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges**](http://www.sciencedirect.com/science/article/pii/S1566253519307377) , (Information Fusion 2020) by *Timothée Lesort, Vincenzo Lomonaco, Andrei Stoian, Davide Maltoni, David Filliat and Natalia Díaz-Rodríguez* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1339-L1350) +- [**Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL**](https://openreview.net/forum?id=HyxAfnA5tm) , (ICLR 2019) by *Anusha Nagabandi, Chelsea Finn and Sergey Levine* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L950-L957) ``` Formulates an online learning procedure that uses SGD to update model parameters, and an EM with a Chinese restaurant process prior to develop and maintain a mixture of models to handle non-stationary task distribution ``` -- **Continual Reinforcement Learning deployed in Real-life using PolicyDistillation and Sim2Real Transfer**, (ICML Workshop 2019) by *Kalifou, René Traoré, Caselles-Dupré, Hugo, Lesort, Timothée, Sun, Te, Diaz-Rodriguez, Natalia and Filliat, David * [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1253-L1259) -- [**Experience replay for continual learning**](https://arxiv.org/abs/1811.11682) , (NeurIPS 2019) by *Rolnick, David, Ahuja, Arun, Schwarz, Jonathan, Lillicrap, Timothy and Wayne, Gregory* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1461-L1469) +- **Continual Reinforcement Learning deployed in Real-life using PolicyDistillation and Sim2Real Transfer**, (ICML Workshop 2019) by *Kalifou, René Traoré, Caselles-Dupré, Hugo, Lesort, Timothée, Sun, Te, Diaz-Rodriguez, Natalia and Filliat, David * [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1271-L1277) +- [**Experience replay for continual learning**](https://arxiv.org/abs/1811.11682) , (NeurIPS 2019) by *Rolnick, David, Ahuja, Arun, Schwarz, Jonathan, Lillicrap, Timothy and Wayne, Gregory* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1479-L1487) - [**PathNet: Evolution Channels Gradient Descent in Super Neural Networks**](http://arxiv.org/abs/1701.08734) , (2017) by *Chrisantha Fernando and Dylan Banarse and Charles Blundell and @@ -355,84 +357,85 @@ Yori Zwols and David Ha and Andrei A. Rusu and Alexander Pritzel and -Daan Wierstra* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1796-L1816) -- **Incremental robot learning of new objects with fixed update time**, (2017) by *R. {Camoriano}, G. {Pasquale}, C. {Ciliberto}, L. {Natale}, L. {Rosasco} and G. {Metta}* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1934-L1946) +Daan Wierstra* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1814-L1834) +- **Incremental robot learning of new objects with fixed update time**, (2017) by *R. {Camoriano}, G. {Pasquale}, C. {Ciliberto}, L. {Natale}, L. {Rosasco} and G. {Metta}* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1952-L1964) ## Task-Agnostic Lifelong Reinforcement Learning -- [**Co{MPS}: Continual Meta Policy Search**](https://openreview.net/forum?id=PVJ6j87gOHz) , (ICLR 2022) by *Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn and Sergey Levine* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L126-L133) +- [**Co{MPS}: Continual Meta Policy Search**](https://openreview.net/forum?id=PVJ6j87gOHz) , (ICLR 2022) by *Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn and Sergey Levine* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L144-L151) ``` Co{MPS} is a novel meta-policy search algorithm for task-agnostic continual RL ``` -- [**Task-Agnostic Continual Reinforcement Learning: In Praise of a Simple Baseline**](https://arxiv.org/abs/2205.14495) , (arXiv 2022) by *Caccia, Massimo, Mueller, Jonas, Kim, Taesup, Charlin, Laurent and Fakoor, Rasool* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L136-L143) +- [**Task-Agnostic Continual Reinforcement Learning: In Praise of a Simple Baseline**](https://arxiv.org/abs/2205.14495) , (arXiv 2022) by *Caccia, Massimo, Mueller, Jonas, Kim, Taesup, Charlin, Laurent and Fakoor, Rasool* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L154-L161) ``` combines replay and an RNN to set a simple baseline for TACRL: shows that the baselines matches and surpasses previously thought upper bounds ``` -- [**Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning**](https://arxiv.org/abs/2207.05742) , (2022) by *Steinparz, Christian, Schmied, Thomas, Paischer, Fabian, Dinu, Marius-Constantin, Patil, Vihang, Bitto-Nemling, Angela, Eghbal-zadeh, Hamid and Hochreiter, Sepp* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3460-L3467) +- [**Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning**](https://arxiv.org/abs/2207.05742) , (2022) by *Steinparz, Christian, Schmied, Thomas, Paischer, Fabian, Dinu, Marius-Constantin, Patil, Vihang, Bitto-Nemling, Angela, Eghbal-zadeh, Hamid and Hochreiter, Sepp* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3478-L3485) ``` Detects changes and explores when and where they happen to recover from non-stationarity. ``` -- [**Same State, Different Task: Continual Reinforcement Learning without Interference**](https://arxiv.org/abs/2106.02940) , (2021) by *Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren and Stephen J. Roberts* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L114-L122) +- [**Same State, Different Task: Continual Reinforcement Learning without Interference**](https://arxiv.org/abs/2106.02940) , (2021) by *Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren and Stephen J. Roberts* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L132-L140) ``` learns multiple policies and cast policy-retrieval as a multi-arm bandit problem ``` -- [**CoMPS: Continual Meta Policy Search**](https://arxiv.org/abs/2112.04467) , (2021) by *Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn and Sergey Levine* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L189-L198) -- [**Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes**](https://arxiv.org/abs/2006.11441) , (2020) by *Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen and Ding Zhao* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L146-L154) +- [**CoMPS: Continual Meta Policy Search**](https://arxiv.org/abs/2112.04467) , (2021) by *Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn and Sergey Levine* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L207-L216) +- [**Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes**](https://arxiv.org/abs/2006.11441) , (2020) by *Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen and Ding Zhao* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L164-L172) ``` uses an infinite mixture of Gaussian Processes to learn a task-agnostic policy ``` -- [**Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL**](https://openreview.net/forum?id=HyxAfnA5tm) , (ICLR 2019) by *Anusha Nagabandi, Chelsea Finn and Sergey Levine* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L932-L939) +- [**Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL**](https://openreview.net/forum?id=HyxAfnA5tm) , (ICLR 2019) by *Anusha Nagabandi, Chelsea Finn and Sergey Levine* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L950-L957) ``` Formulates an online learning procedure that uses SGD to update model parameters, and an EM with a Chinese restaurant process prior to develop and maintain a mixture of models to handle non-stationary task distribution ``` ## Continual Generative Modeling -- [**Continual Unsupervised Representation Learning**](https://arxiv.org/pdf/1910.14481.pdf) , (2019) by *Dushyant Rao, Francesco Visin, Andrei A. Rusu, Yee Whye Teh, Razvan Pascanu and Raia Hadsell* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L942-L951) +- [**Continual Unsupervised Representation Learning**](https://arxiv.org/pdf/1910.14481.pdf) , (2019) by *Dushyant Rao, Francesco Visin, Andrei A. Rusu, Yee Whye Teh, Razvan Pascanu and Raia Hadsell* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L960-L969) ``` Introduces unsupervised continual learning (no task label and no task boundaries) ``` -- [**Generative Models from the perspective of Continual Learning**](https://hal.archives-ouvertes.fr/hal-01951954) , (IJCNN 2019) by *Lesort, Timothée, Caselles-Dupré, Hugo, Garcia-Ortiz, Michael, Goudou, Jean-Fran{\c c}ois and Filliat, David* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L954-L966) +- [**Generative Models from the perspective of Continual Learning**](https://hal.archives-ouvertes.fr/hal-01951954) , (IJCNN 2019) by *Lesort, Timothée, Caselles-Dupré, Hugo, Garcia-Ortiz, Michael, Goudou, Jean-Fran{\c c}ois and Filliat, David* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L972-L984) ``` Extensive evaluation of CL methods for generative modeling ``` -- [**Closed-loop Memory GAN for Continual Learning**](http://dl.acm.org/citation.cfm?id=3367471.3367504) , (IJCAI 2019) by *Rios, Amanda and Itti, Laurent* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1261-L1275) -- [**Lifelong Generative Modeling**](https://arxiv.org/abs/1705.09847) , (arXiv 2017) by *Ramapuram, Jason, Gregorova, Magda and Kalousis, Alexandros* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L969-L976) +- [**Closed-loop Memory GAN for Continual Learning**](http://dl.acm.org/citation.cfm?id=3367471.3367504) , (IJCAI 2019) by *Rios, Amanda and Itti, Laurent* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1279-L1293) +- [**Lifelong Generative Modeling**](https://arxiv.org/abs/1705.09847) , (arXiv 2017) by *Ramapuram, Jason, Gregorova, Magda and Kalousis, Alexandros* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L987-L994) ## Biologically-Inspired -- [**Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic Environments**](https://www.frontiersin.org/articles/10.3389/fnbot.2022.846219/full) , (2022) by *Iyer, Abhiram, Grewal, Karan, Velu, Akash, Souza, Lucas Oliveira, Forest, Jeremy and Ahmad, Subutai* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L77-L86) +- [**Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic Environments**](https://www.frontiersin.org/articles/10.3389/fnbot.2022.846219/full) , (2022) by *Iyer, Abhiram, Grewal, Karan, Velu, Akash, Souza, Lucas Oliveira, Forest, Jeremy and Ahmad, Subutai* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L95-L104) ``` bio-inspired method which dynamically restrict and route information in a context-specific manner ``` -- [**A rapid and efficient learning rule for biological neural circuits**](https://www.biorxiv.org/content/10.1101/2021.03.10.434756v1.full.pdf) , (2021) by *Eren Sezener, Agnieszka Grabska-Barwinska, Dimitar Kostadinov, Maxime Beau, Sanjukta Krishnagopal, David Budden, Marcus Hutter, Joel Veness, Matthew M. Botvinick, Claudia Clopath, Michael H{\"a}usser and Peter E. Latham* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L104-L111) -- [**Alleviating catastrophic forgetting using context-dependent gating and synaptic stabilization**](https://www.pnas.org/doi/pdf/10.1073/pnas.1803839115) , (2018) by *Masse, Nicolas Y, Grant, Gregory D and Freedman, David J* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L90-L101) +- [**A rapid and efficient learning rule for biological neural circuits**](https://www.biorxiv.org/content/10.1101/2021.03.10.434756v1.full.pdf) , (2021) by *Eren Sezener, Agnieszka Grabska-Barwinska, Dimitar Kostadinov, Maxime Beau, Sanjukta Krishnagopal, David Budden, Marcus Hutter, Joel Veness, Matthew M. Botvinick, Claudia Clopath, Michael H{\"a}usser and Peter E. Latham* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L122-L129) +- [**Alleviating catastrophic forgetting using context-dependent gating and synaptic stabilization**](https://www.pnas.org/doi/pdf/10.1073/pnas.1803839115) , (2018) by *Masse, Nicolas Y, Grant, Gregory D and Freedman, David J* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L108-L119) ``` a network trained to do CL where select subnetworks are used to learn each task; these subnetworks are chosen a priori ``` ## Miscellaneous -- [**Learning causal models online**](https://arxiv.org/abs/2006.07461) , (arXiv 2020) by *Javed, Khurram, White, Martha and Bengio, Yoshua* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L237-L244) +- [**Learning causal models online**](https://arxiv.org/abs/2006.07461) , (arXiv 2020) by *Javed, Khurram, White, Martha and Bengio, Yoshua* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L255-L262) ## Applications -- [**On the Limitations of Continual Learning for Malware Classification**](https://arxiv.org/abs/2208.06568) , (2022) by *Rahman, Mohammad Saidur, Coull, Scott E and Wright, Matthew* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L21-L28) +- [**MRN: Multiplexed Routing Network for Incremental Multilingual Text Recognition**](https://arxiv.org/abs/2305.14758) , (ICCV 2023) by *Zheng, Tianlun, Chen, Zhineng, Huang, BingChen, Zhang, Wei and Jiang, Yu-Gang* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L19-L26) +- [**On the Limitations of Continual Learning for Malware Classification**](https://arxiv.org/abs/2208.06568) , (2022) by *Rahman, Mohammad Saidur, Coull, Scott E and Wright, Matthew* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L39-L46) ``` This paper investigates overcoming catastrophic forgetting for malware classification ``` -- [**CLOPS: Continual Learning of Physiological Signals**](https://arxiv.org/abs/2004.09578) , (arXiv 2020) by *Kiyasseh, Dani, Zhu, Tingting and Clifton, David A* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L404-L411) +- [**CLOPS: Continual Learning of Physiological Signals**](https://arxiv.org/abs/2004.09578) , (arXiv 2020) by *Kiyasseh, Dani, Zhu, Tingting and Clifton, David A* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L422-L429) ``` a healthcare-specific replay-based method to mitigate destructive interference during continual learning ``` -- [**LAMAL: LAnguage Modeling Is All You Need for Lifelong Language Learning**](https://openreview.net/forum?id=Skgxcn4YDS) , (ICLR 2020) by *Fan-Keng Sun, Cheng-Hao Ho and Hung-Yi Lee* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1522-L1529) -- [**Compositional Language Continual Learning**](https://openreview.net/forum?id=rklnDgHtDS) , (ICLR 2020) by *Yuanpeng Li, Liang Zhao, Kenneth Church and Mohamed Elhoseiny* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1551-L1558) +- [**LAMAL: LAnguage Modeling Is All You Need for Lifelong Language Learning**](https://openreview.net/forum?id=Skgxcn4YDS) , (ICLR 2020) by *Fan-Keng Sun, Cheng-Hao Ho and Hung-Yi Lee* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1540-L1547) +- [**Compositional Language Continual Learning**](https://openreview.net/forum?id=rklnDgHtDS) , (ICLR 2020) by *Yuanpeng Li, Liang Zhao, Kenneth Church and Mohamed Elhoseiny* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1569-L1576) ``` method for compositional continual learning of sequence-to-sequence models ``` -- [**Incremental Lifelong Deep Learning for Autonomous Vehicles**](https://ieeexplore.ieee.org/document/8569992) , (2018) by *Pierre, John M.* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L212-L223) -- [**Unsupervised real-time anomaly detection for streaming data**](https://www.sciencedirect.com/science/article/pii/S0925231217309864) , (2017) by *Ahmad, Subutai, Lavin, Alexander, Purdy, Scott and Agha, Zuha* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L377-L387) +- [**Incremental Lifelong Deep Learning for Autonomous Vehicles**](https://ieeexplore.ieee.org/document/8569992) , (2018) by *Pierre, John M.* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L230-L241) +- [**Unsupervised real-time anomaly detection for streaming data**](https://www.sciencedirect.com/science/article/pii/S0925231217309864) , (2017) by *Ahmad, Subutai, Lavin, Alexander, Purdy, Scott and Agha, Zuha* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L395-L405) ``` HTM applied to real-world anomaly detection problem ``` -- [**Continuous online sequence learning with an unsupervised neural network model**](https://arxiv.org/abs/1512.05463) , (2016) by *Cui, Yuwei, Ahmad, Subutai and Hawkins, Jeff* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L390-L401) +- [**Continuous online sequence learning with an unsupervised neural network model**](https://arxiv.org/abs/1512.05463) , (2016) by *Cui, Yuwei, Ahmad, Subutai and Hawkins, Jeff* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L408-L419) ``` HTM applied to a prediction problem of taxi passenger demand ``` ## Thesis -- [**Continual Learning: Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes**](https://arxiv.org/abs/2007.00487) , (2020) by *Timothée Lesort* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L337-L346) -- [**Continual Learning with Deep Architectures**](http://amsdottorato.unibo.it/9073/1/vincenzo_lomonaco_thesis.pdf) , (2019) by *Vincenzo Lomonaco* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1688-L1694) -- [**Continual Learning in Neural Networks**](https://arxiv.org/abs/1910.02718) , (arXiv 2019) by *Aljundi, Rahaf* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2160-L2167) -- [**Continual learning in reinforcement environments**](https://www.cs.utexas.edu/~ring/Ring-dissertation.pdf) , (1994) by *Ring, Mark Bishop* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1761-L1768) +- [**Continual Learning: Tackling Catastrophic Forgetting in Deep Neural Networks with Replay Processes**](https://arxiv.org/abs/2007.00487) , (2020) by *Timothée Lesort* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L355-L364) +- [**Continual Learning with Deep Architectures**](http://amsdottorato.unibo.it/9073/1/vincenzo_lomonaco_thesis.pdf) , (2019) by *Vincenzo Lomonaco* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1706-L1712) +- [**Continual Learning in Neural Networks**](https://arxiv.org/abs/1910.02718) , (arXiv 2019) by *Aljundi, Rahaf* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2178-L2185) +- [**Continual learning in reinforcement environments**](https://www.cs.utexas.edu/~ring/Ring-dissertation.pdf) , (1994) by *Ring, Mark Bishop* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1779-L1786) ## Libraries -- [**Renate: a library for real-world continual learning**](https://github.com/awslabs/renate) , (2022) by ** [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3470-L3478) +- [**Renate: a library for real-world continual learning**](https://github.com/awslabs/renate) , (2022) by ** [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3488-L3496) ``` A library for real-world continual learning with integrated hyperparameter tuning. ``` -- [**Sequoia - Towards a Systematic Organization of Continual Learning Research**](https://github.com/lebrice/Sequoia) , (2021) by *Fabrice Normandin, Florian Golemo, Oleksiy Ostapenko, Matthew Riemer, Pau Rodriguez, Julio Hurtado, Khimya Khetarpal, Timothée Lesort, Laurent Charlin, Irina Rish and Massimo Caccia* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2951-L2960) +- [**Sequoia - Towards a Systematic Organization of Continual Learning Research**](https://github.com/lebrice/Sequoia) , (2021) by *Fabrice Normandin, Florian Golemo, Oleksiy Ostapenko, Matthew Riemer, Pau Rodriguez, Julio Hurtado, Khimya Khetarpal, Timothée Lesort, Laurent Charlin, Irina Rish and Massimo Caccia* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2969-L2978) ``` A library that unifies Continual Supervised and Continual Reinforcement Learning research ``` -- [**Avalanche: an End-to-End Library for Continual Learning**](https://avalanche.continualai.org/) , (2021) by *Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Gabriele Graffieti and Antonio Carta* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2973-L2981) +- [**Avalanche: an End-to-End Library for Continual Learning**](https://avalanche.continualai.org/) , (2021) by *Vincenzo Lomonaco, Lorenzo Pellegrini, Andrea Cossu, Gabriele Graffieti and Antonio Carta* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2991-L2999) ``` A library for Continual Supervised Learning ``` -- [**Continuous Coordination As a Realistic Scenario for Lifelong Learning**](https://github.com/chandar-lab/Lifelong-Hanabi) , (2021) by *Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron Courville and Sarath Chandar* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2984-L2993) +- [**Continuous Coordination As a Realistic Scenario for Lifelong Learning**](https://github.com/chandar-lab/Lifelong-Hanabi) , (2021) by *Hadi Nekoei, Akilesh Badrinaaraayanan, Aaron Courville and Sarath Chandar* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L3002-L3011) ``` a multi-agent lifelong learning testbed that supports both zero-shot and few-shot settings. ``` - **River: machine learning for streaming data in Python**, (2020) by *Jacob Montiel, Max Halford, Saulo Martiello Mastelini and Geoffrey Bolmier, Raphael Sourty, Robin Vaysse and Adil Zouitine, Heitor Murilo Gomes, Jesse Read -and Talel Abdessalem and Albert Bifet* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2606-L2617) +and Talel Abdessalem and Albert Bifet* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2624-L2635) ``` A library for online learning. ``` -- **Continuum, Data Loaders for Continual Learning**, (2020) by *Douillard, Arthur and Lesort, Timothée* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2620-L2628) +- **Continuum, Data Loaders for Continual Learning**, (2020) by *Douillard, Arthur and Lesort, Timothée* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2638-L2646) ``` A library proposing continual learning scenarios and metrics. ``` -- [**Framework for Analysis of Class-Incremental Learning**](https://github.com/mmasana/FACIL) , (arXiv 2020) by *Masana, Marc, Liu, Xialei, Twardowski, Bartlomiej, Menta, Mikel, Bagdanov, Andrew D and van de Weijer, Joost* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2963-L2970) +- [**Framework for Analysis of Class-Incremental Learning**](https://github.com/mmasana/FACIL) , (arXiv 2020) by *Masana, Marc, Liu, Xialei, Twardowski, Bartlomiej, Menta, Mikel, Bagdanov, Andrew D and van de Weijer, Joost* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2981-L2988) ``` A library for Continual Class-Incremental Learning ``` ## Workshops -- [**Workshop on Continual Learning at ICML 2020**](https://sites.google.com/view/cl-icml/organizers?authuser=0) , (2020) by *Rahaf Aljundi, Haytham Fayek, Eugene Belilovsky, David Lopez-Paz, Arslan Chaudhry, Marc Pickett, Puneet Dokania, Jonathan Schwarz and Sayna Ebrahimi* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L348-L355) -- [**4th Lifelong Machine Learning Workshop at ICML 2020**](https://openreview.net/group?id=ICML.cc/2020/Workshop/LifelongML#accept) , (2020) by *Shagun Sodhani, Sarath Chandar, Balaraman Ravindran and Doina Precup* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L358-L365) -- **CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions**, (arXiv 2020) by *Lomonaco, Vincenzo, Pellegrini, Lorenzo, Rodriguez, Pau, Caccia, Massimo, She, Qi, Chen, Yu, Jodelet, Quentin, Wang, Ruiping, Mai, Zheda, Vazquez, David and others* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1562-L1568) +- [**Workshop on Continual Learning at ICML 2020**](https://sites.google.com/view/cl-icml/organizers?authuser=0) , (2020) by *Rahaf Aljundi, Haytham Fayek, Eugene Belilovsky, David Lopez-Paz, Arslan Chaudhry, Marc Pickett, Puneet Dokania, Jonathan Schwarz and Sayna Ebrahimi* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L366-L373) +- [**4th Lifelong Machine Learning Workshop at ICML 2020**](https://openreview.net/group?id=ICML.cc/2020/Workshop/LifelongML#accept) , (2020) by *Shagun Sodhani, Sarath Chandar, Balaraman Ravindran and Doina Precup* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L376-L383) +- **CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions**, (arXiv 2020) by *Lomonaco, Vincenzo, Pellegrini, Lorenzo, Rodriguez, Pau, Caccia, Massimo, She, Qi, Chen, Yu, Jodelet, Quentin, Wang, Ruiping, Mai, Zheda, Vazquez, David and others* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L1580-L1586) ``` surveys the results of the first CL competition at CVPR ``` -- [**1st Lifelong Learning for Machine Translation Shared Task at WMT20 (EMNLP 2020)**](http://www.statmt.org/wmt20/lifelong-learning-task.html) , (2020) by *Loïc Barrault, Magdalena Biesialska, Marta R. Costa-jussà, Fethi Bougares and Olivier Galibert* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2789-L2791) +- [**1st Lifelong Learning for Machine Translation Shared Task at WMT20 (EMNLP 2020)**](http://www.statmt.org/wmt20/lifelong-learning-task.html) , (2020) by *Loïc Barrault, Magdalena Biesialska, Marta R. Costa-jussà, Fethi Bougares and Olivier Galibert* [[bib]](https://github.com/optimass/continual_learning_papers/blob/master/bibtex.bib#L2807-L2809) From 413ae7bda05684916cbd9fe5eb91a71a08b7b499 Mon Sep 17 00:00:00 2001 From: simplify <39580716+simplify23@users.noreply.github.com> Date: Tue, 25 Jul 2023 09:22:31 +0800 Subject: [PATCH 2/2] Update bibtex.bib --- bibtex.bib | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/bibtex.bib b/bibtex.bib index 84a43b9..80e58f8 100644 --- a/bibtex.bib +++ b/bibtex.bib @@ -6,6 +6,15 @@ @article{rebuffi2017learning year={2017} } +@inproceedings{zheng2023mrn, + title={MRN: Multiplexed Routing Network for Incremental Multilingual Text Recognition}, + author={Zheng, Tianlun and Chen, Zhineng and Huang, BingChen and Zhang, Wei and Jiang, Yu-Gang}, + booktitle={ICCV}, + year={2023}, + url={https://arxiv.org/abs/2305.14758}, + keywords={Applications, Rehearsal, Routing, New Settings or Metrics} +} + @inproceedings{bonicelli2022effectiveness, title={On the Effectiveness of Lipschitz-Driven Rehearsal in Continual Learning}, author={Bonicelli, Lorenzo and Boschini, Matteo and Porrello, Angelo and Spampinato, Concetto and Calderara, Simone},