Merge pull request #903 from Parallel-in-Time/bibtex-bibbot-902-8395bb7

pint.bib updates

Author: pancetta

_bibliography/pint.bib

@@ -7586,6 +7586,20 @@ @article{JinEtAl2025
 	year = {2025},
 }
 
+@article{L2025,
+	author = {L, D’Amore},
+	doi = {10.17352/tcsit.000091},
+	issn = {2641-3086},
+	journal = {Trends in Computer Science and Information Technology},
+	number = {2},
+	pages = {007–010},
+	publisher = {Peertechz Publications Private Limited},
+	title = {A Model Decomposition-in-Time of Recurrent Neural Networks: A Feasibility Analysis},
+	url = {http://dx.doi.org/10.17352/tcsit.000091},
+	volume = {10},
+	year = {2025},
+}
+
 @unpublished{LaidinEtAl2025,
 	abstract = {We present the design of a multiscale parareal method for kinetic equations in the fluid dynamic regime. The goal is to reduce the cost of a fully kinetic simulation using a parallel in time procedure. Using the multiscale property of kinetic models, the cheap, coarse propagator consists in a fluid solver and the fine (expensive) propagation is achieved through a kinetic solver for a collisional Vlasov equation. To validate our approach, we present simulations in the 1D in space, 3D in velocity settings over a wide range of initial data and kinetic regimes, showcasing the accuracy, efficiency, and the speedup capabilities of our method.},
 	author = {Tino Laidin and Thomas Rey},