v0.25.0

✨ Highlights

🚀 New Inference Methods

• MNPE class mixed parameter (similar to MNLE) by @dgedon in #1362
• Implementation of SNPE-B (#199) by @etouron1 in #1471

🧠 Neural Network Architectures & Embedding Networks

• Add transformer embedding net by @NicolasRR in #1494
• Add embedding net that uses 1D causal convolutions (#1459) by @Aranka-S in #1499
• Add LRU-backed embedding networks by @famura in #1512
• Add ResNet as embedding model by @StefanWahl in #1472
• Spectral convolution embedding net by @L-in-da in #1503

⭐ Major Features & Capabilities

• Unify flow matching and score-based models by @StarostinV in #1497
• Model misspecification detection based on MMD by @coschroeder in #1502
• Marginal estimator log-prob based test for misspecification by @swag2198 in #1522
• Adding interface for unconditional flow training by @plcrodrigues in #1470
• Support using trained estimators in Pyro models by @sethaxen in #1491
• Add util to generate mcmc samples from user defined potential (#1405) by @hayden-johnson in #1483
• Logit transform by @anastasiakrouglova in #1485
• Log-prob for iid data for score estimators by @Kartik-Sama in #1508

📚 Documentation & Tutorials

• Tutorial on new features for score-based methods #1392 by @touronc in #1489
• Docs: Introduce Readthedocs website by @michaeldeistler in #1463

🐛 Bug Fixes

• z_score correct order in Zuko by @anastasiakrouglova in #1492
• Minor fix when moving thetas from GPU to CPU by @famura in #1515
• Minor fix while using unconditional density estimator and LRU embedding by @ARna06 in #1556
• fix: replace 'in' operator with '==' for proper classifier comparison by @abelaba in #1550
• flowmatching condition shape fix by @gmoss13 in #1584
• patch for torch bug in tarp, run torch.histogram with cpu-only tensor by @psteinb in #1596
• fix failing tarp test by @janfb in #1628
• fix: cap max_sampling_batch_size to prevent excessive memory by @janfb in #1624
• 1561 computation of denoising posterior precision matrix in jac method score fn iid by @manuelgloeckler in #1636
• fix xfail test, fix deprecation warnings by @janfb in #1642
• fix: iid-score device handling by @janfb in #1650
• fix: fmpe singularity on sde sampling by @manuelgloeckler in #1661

🛠️ Maintenance & Improvements

🔧 Code Quality & Refactoring

• Refactoring flow and score matching classes and nets by @manuelgloeckler in #1544
• Rename inference trainer classes by @abelaba in #1605
• Rename VectorFieldInference to VectorFieldTrainer by @abelaba in #1614
• Refactor build_posterior to Eliminate Duplication Across Trainers by @abelaba in #1610
• Refactor build posterior method arguments to use Literals by @abelaba in #1606
• Refactor build_posterior Posterior Configuration Using Dataclasses by @abelaba in #1619
• Use TypeAlias and consistent naming for sbi types by @janfb in #1637
• Add protocol for estimator builder by @abelaba in #1633
• Improve abc implementation by @janfb in #1615
• Refactor RatioEstimator to subclass ConditionalEstimator @abelaba in #1652

🏷️ Type Hints & API Improvements

• fix: add enum for flow options to fix type hints. by @janfb in #1562
• fix LC2ST kwarg typing by @janfb in #1565
• fix: Update RatioEstimator classifier argument to use a Protocol by @abelaba in #1582
• Update append_simulations return type to Self by @abelaba in #1622
• Deprecation Warnings for build_posterior stringly typed parameters by @abelaba in #1627

🧪 Testing & CI/CD

• Testmon by @manuelgloeckler in #1452
• disable testmon for now by @manuelgloeckler in #1467
• chore: Use pytest-split plugin in ci workflow by @schroedk in #1465
• tests: refactor "not slow" tests to be not so slow by @janfb in #1495
• Test for known pytorch distribution transform issue by @dgedon in #1504
• xfail scan test on python 3.13 by @manuelgloeckler in #1533
• Gpu test for VectorFieldPosterior by @jorobledo in #1542
• set vector field iid-tests xfail by @janfb in #1554
• Changed the xfail condition for LRU tests with mode='scan' by @famura in #1552
• Fix/lru test by @Matthijspals in #1568
• refactor sbc funcs and tests by @janfb in #1578
• chore: remove testmon, add codecov test analytics by @janfb in #1592
• chore: reorder setup steps for Python and uv in CI/CD workflows by @janfb in #1601
• Fix/lc2st numpy type fixes by @janfb in #1613
• Fix failing CI on main. by @janfb in #1618
• Fix slow vector field tests by @janfb in #1657
• Add tests for sensitivity analysis by @janfb in #1662

📖 Documentation & Website

• Fix tests for new docs by @michaeldeistler in #1475
• Prevent notebook execution upon doc build by @michaeldeistler in #1477
• Fix broken links on website by @michaeldeistler in #1480
• fix: Update documentation folder path by @abelaba in #1510
• fix path to contribute.md by @psteinb in #1507
• Add utils to docs by @sethaxen in #1520
• Update new Readthedocs website by @michaeldeistler in #1519
• fix broken links on new website by @michaeldeistler in #1538
• Fixups for new website landing page by @michaeldeistler in #1539
• Fix: add tutorial page to mkdocs website by @michaeldeistler in #1540
• Fix broken links in some tutorials by @michaeldeistler in #1541
• Add examples to documentation by @jorobledo in #1548
• docs: Add importance_sampling_parameters to build_posterior docstring. by @abelaba in #1558
• Add missing arguments to LikelihoodEstimator and RatioEstimator docstrings. by @abelaba in #1571
• Fixups for new RTD website by @michaeldeistler in #1573
• Tutorial with a more representative training loop by @michaeldeistler in #1574
• Fixups for rendering of HH tutorial notebook by @michaeldeistler in #1575
• fix for colors in Hodgkin-Huxley notebook by @michaeldeistler in #1576
• Add citations to how-to guide by @michaeldeistler in #1579
• Clarify fullscreen view of applications-explorer by @michaeldeistler in #1580
• Fixups for the documentation by @michaeldeistler in #1585
• fixed misrendered bullet list, tested locally by @psteinb in #1594
• Improvements to L-C2ST tutorial by @michaeldeistler in #1588
• docs: Change colortheme in light mode by @michaeldeistler in #1638
• Posterior parameters doc by @abelaba in #1644
• fix contributing links by @janfb in #1647
• docs: add posterior parameters dataclass how to guide by @abelaba in #1654

🏗️ Infrastructure & Dependencies

• Add uv support by @abelaba in #1518
• switch to numfocus code of conduct by @janfb in #1560
• Update readme with new JOSS citation by @janfb in #1564
• update numfocus code of conduct by @janfb in #1602
• Added Apache License reference co...

v0.24.0

✨ Highlights

• feat: add CategoricalMADE by @jnsbck in #1269 (Major New Feature)
• tests: mini-sbibm by @manuelgloeckler in #1335 (Major New Feature)
• feat: Score-based iid sampling by @manuelgloeckler in #1381 (Major New Feature)
• Drop python3.9 support, fix ci by @janfb in #1412 (Python Version Support Change)
• additional features for NPSE by @gmoss13 in #1370 (Enhancement)

🐛 Bug Fixes

• fix: leakage correction breaks consistency of log prob vs log prob batched by @manuelgloeckler in #1355
• fix #1343 device handling in mog_log_prob by @janfb in #1356
• Fix failing tutorials, change MNLE default for log_transform to False by @janfb in #1367
• Fix conditional posterior shape and device bugs. by @janfb in #1373
• fix: type fix in VI subclasses. xfail pymc tests. by @janfb in #1390
• Temporary Wrappers to fix MADE by @gmoss13 in #1398
• Fix mnle tests, MCMC init pbar, sir batch size. by @janfb in #1410
• fix mnle tests by @janfb in #1415
• fix: protocol and refactor for custom potential by @janfb in #1409
• fix docs workflow by @janfb in #1419
• fix: gpu-handling for CategoricalMADE by @janfb in #1448

🛠️ Maintenance & Improvements

• increase tutorial test timeout by @janfb in #1360
• add nan check to _loss method. by @janfb in #1361
• Update and pin pre commit and ruff to recent version. by @janfb in #1358
• add nan handling in diagnostics by @janfb in #1359
• Improve tests to detect circular imports and resolve all of them by @manuelgloeckler in #1357
• docs: add details about zuko density estimators by @janfb in #1387
• fix: duplication of 'large number' in warning by @turnmanh in #1391
• improve PR and issue templates by @janfb in #1399
• perf: speed up CI with uv by @janfb in #1400
• tests: add pytest testmon plugin to speed up CI by @janfb in #1402
• small fixes to score methods by @janfb in #1404
• docs: Corrected python version in installation document (Revised) by @VijaySamant4368 in #1423
• docs: Markdown formatting compliant to Markdown Linter (solves #1434) by @nMaax in #1443

🎉 New Contributors

• @VijaySamant4368 made their first contribution in #1423
• @nMaax made their first contribution in #1443

Full Changelog: v0.23.3...v0.24.0

v0.23.3

v0.23.3

Highlights 🤩

• docs: Add conda-forge install instructions by @matthewfeickert in #1340
• feat: NLE with multiple iid conditions by @janfb in #1331

What's Changed 🚧

• fix: Correted typo in y-axis label by @turnmanh in #1296
• docs: update embedding networks notebook by @emmanuel-ferdman in #1297
• fix pickle issues in MCMC posterior + test by @manuelgloeckler in #1291
• Minor fix for EnsemblePosterior weights.setter by @CompiledAtBirth in #1299
• Remove deprecated neural_net access from utils by @tvwenger in #1302
• [test] add tests for ensemble posterior weights by @samadpls in #1307
• Clarify last round behavior of SNPE-A by @michaeldeistler in #1323
• expose batched sampling option; error handling by @janfb in #1321
• Fix #1316: remove sample_dim docstring for condition. by @janfb in #1338
• docs: fix tutorial typos by @janfb in #1341
• docs: run and seed SBC tutorial by @manuel-morales-a in #1336

New Contributors 🎉

• @emmanuel-ferdman made their first contribution in #1297
• @CompiledAtBirth made their first contribution in #1299
• @tvwenger made their first contribution in #1302
• @matthewfeickert made their first contribution in #1340
• @manuel-morales-a made their first contribution in #1336

Full Changelog: v0.23.2...v0.23.3

v0.23.2

Bug Fixes

• fixup for failing hmc test by @michaeldeistler (#1247)
• fix: make RestrictedPrior a distribution to enable log_prob @janfb (#1257)
• fix: npe iid handling by @janfb (#1262)
• fix: tutorials test error handling, fix bugs in tutorials by @janfb (#1264)
• fix #1260: include points in plotting limits by @janfb (#1265)
• fix: conditioned potential error handling by @janfb, @michaeldeistler (#1275, #1289)
• fix: Allow 1D pytorch distributions by @michaeldeistler (#1286)

Documentation

• Rename SNPE to NPE in the README by @michaeldeistler (#1248)
• update pickling FAQ by @michaeldeistler (#1255)
• Adding example for custom DataLoader to tutorial 18 by @psteinb (#1256)
• docs: add readme intro to docs landing page by @janfb (#1272)
• Change sampling method for LC2ST to sample_batched() by @JuliaLinhart (#1279)

Maintenance

• Refactor simulate_for_sbi location by @samadpls (#1253)
• build: devcontainer update by @janfb (#1252)
• fix: docker notebook python version by @janfb (#1258)
• refactor: remove outputs except plots from tutorials. by @janfb (#1266)
• build: automatic nb stripping and pypi upload by @janfb (#1267)
• refactor: remove deprecated x_shape where not needed by @janfb (#1271)
• more explicit error message for CNN shapes by @Ankush7890 (#1281)

v0.23.1

• fix: include score folder by adding __init__.py (#1245 #1246)

v0.23.0

Announcements

• Re-licensing: license change from
  AGPLv3 to
  Apache-2.0 (see #997 for
  details)
• sbi is now affiliated with NumFOCUS 🎉
• New contributors 🎉: @anastasiakrouglova, @theogruner, @felixp8, @Matthijspals,
  @jsvetter, @pfuhr, @turnmanh, @fariedabuzaid, @augustes, @zinaStef, @Baschdl,
  @danielmk, @lisahaxel, @janko-petkovic, @samadpls, @ThomasGesseyJonesPX, @schroedk

Major Changes

• internal renaming of all inference classes from, e.g., SNPE to NPE (i.e., we
  removed the S prefix). The functionality of the classes remains the same. The NPE
  class handles both the amortized and sequential versions of neural posterior
  estimation. An alias for SNPE (and other sequential methods) still exists for
  backwards compatibility (#1238) (@michaeldeistler).
• change sbi default parameters: training_batch_size=200, num_chains=20 (#1221)
  (@janfb)
• change imports of posterior_nn, likelihood_nn, and classifier_nn. They should
  now be imported from sbi.neural_nets, not from sbi.utils (#994) (@famura)
• big refactoring of plotting utilities, new tutorial (#1084) (@Matthijspals)
• improved tutorials and website documentation (#1012, #1051, #1073) (@augustes,
  @zinaStef, @lisahaxel, @psteinb)
• improved website structure and contribution guides (#1019) (@tomMoral, @janfb)
• drop support for python3.8 and torch1.12 (#1233)
• refactor folder structure and naming of neural_nets (#1237) (@michaeldeistler)

New Features

• full flexibility over the training loop (#983) (@michaeldeistler)
• unified density estimator classes (#952, #965, #979, #1151) (@michaeldeistler,
  @gmoss13, @tomMoral, @manualgloeckler)
• vectorized sampling and log_prob for (S)NPE given batches of x (#1153)
  (@manuelgloeckler, @michaeldeistler)
• batched sampling for vectorized MCMC samplers (#1176, #1210) (@gmoss13, @janfb)
• support @Zuko as a backend for normalizing flows (#1088, #1116)
  (@anastasiakrouglova)
• local c2st metric (#1109) (@JuliaLinhart)
• tarp coverage metric (#1106) (@psteinb)
• add interface for @pymc samplers (#1053) (@famura, @felixp8)
• flow matching density estimators (#1049) (@turnmanh, @fariedabuzaid, @janfb)
• score matching density estimators (#1015) (@rdgao, @jsvetter, @pfuhr,
  @manuelgloeckler, @michaeldeistler, @janfb)
• ABC methods for trial-based data using statistical distances (#1104)
  (@theogruner)
• support Apple MPS as gpu device (#912) (@janfb)
• dev container for using sbi in codespaces on GitHub (#1070) (@turnmanh)
• enable importance sampling for likelihood-based estimators (#1183) (@manuelgloeckler)
• refactoring and unified shape handling for RatioEstimator (#1097) (@bkmi)
• faster sbc and tarp calibration checks via batched sampling (#1196) (@janfb)
• batched sampling and embedding net support for MNLE (#1203) (@janfb)
• adapt MNLE to new densitye stimator abstraction (#1089) (@coschroeder)
• better plotting options for coverage plots (#1039, #1212) (@janfb)
• allow for potential_fn to be a Callable (#943) (@michaeldeistler)

Bug Fixes

• bugfix for embedding net tutorial (#1159) (@Deismic)
• Fixup for process_x in EnsemblePosterior (#1148) (@Deismic)
• fixed notebook by changing MCMC parameters (#1058) (@zinaStef)
• fix: add NeuralPosteriorEnsemble to utils.init (#1002) (@jnsbck)
• fix: print_false_positive_rate (#976) (@danielmk)
• fix: make VIPosterior pickable (#951) (@manuelgloeckler)
• fix: bug in importance sampled posterior (#1081) (@max-dax)
• fix: embedding device and warning handling (#1186) (@janfb)
• fix: c2st with constant features (#1204) (@janfb)
• fix: erroneous warnings about different devices (#1225, @ThomasGesseyJonesPX)
• fix: type annotation in class ConditionedPotential (#1222) (@schroedk)

Maintenance and other changes

• add pre-commit hooks (#955) (@janfb)
• add ruff to replace isort, black, flake (#960, #978, #1113) (@janfb)
• switch to pyproject.toml for package specification (#941) (@janfb)
• Split the GitHub workflow in CI and CD (#1063) (@famura)
• split linting process from the CI/CD workflow (#1164) (@tomMoral)
• Switch to the newest pyright and fix all typing errors (#1045, #1108) (@Baschdl)
• introduce two docs versions: latest pointing to latest release at
  https://sbi-dev.github.io/sbi/latest/ and dev pointing to the latest version on
  main https://sbi-dev.github.io/sbi/dev/

v0.22.0

API change

• We have moved sbi to an new github organization: https://github.com/sbi-dev/sbi
• We have changed the website of the sbi docs: https://sbi-dev.github.io/sbi/.
• sbi.analysis.pairplot: upper was replaced by offdiag and will be deprecated in a future release.

Features and enhancements

• size-invariant embedding nets for amortized inference with iid-data (@janfb, #808)
• option for new using MAF with rational quadratic splines (thanks to @ImahnShekhzadeh, #819)
• improved docstring for process_prior (thanks to @musoke, #813)
• extended tutorial for SBI with iid data (@janfb, #857)
• new tutorial for SBI with experimental conditions and mixed data (@janfb, #829)
• New options for pairplot:
  • upper is now called offdiag to match other kwargs.
  • alternating colors for samples and points
  • option to add a legend and pass kwargs for the legend.

Bug fixes

• fixed memory leak in in append_simulations (thanks to @VictorSven, #803)
• bug fix for CNRE (thanks to @bkmi, #815)
• bug fix for iid-inference with posterior ensembles (@janfb, #826)
• bug fix for simulation-based calibration with VI posteriors (@janfb, #834, #838)
• bug fix for BoxUniform device handling (@janfb, #854, #856)
• bug fix for MAP estimates with independent priors (@janfb, #867)
• bug fix for tutorial on SBC (@michaeldeistler, #891)
• fix spurious seeding for simulate_for_sbi (@jan-matthis, #876)
• bump python version of github action tests to 3.9.13 (@michaeldeistler, #888, #900)

v0.21.0

• implementation of "Contrastive Neural Ratio Estimation" (thanks to @bkmi, #787)
• implementation of "Balanced Neural Ratio Estimation" (thanks to @ADelau, #779)
• bugfixes for SBC, device handling and handling of iid-observations (#793, #789, #780)

v0.20.0

Major changes and bug fixes

• implementation of "Truncated proposals for scalable and hassle-free sbi" (#754)
• sample-based expected coverage tests (#754)
• permutation invariant embedding to allow iid data in SNPE (thanks @coschroeder, #751)
• convolutional neural network embedding (thanks @coschroeder, #745, #751, #769)
• disallow invalid simulations when using SNLE, SNRE, or atomic SNPE-C (#768)

Enhancements

• add tutorial on all available methods (#754)
• allow seeding of simulate_for_sbi on multiple workers (#762)
• expose enable_transforms in sampler interface (#756)
• bugfix for building the transformation of transformed distributions (#756)

v0.19.2

• Rely on new version of pyknos with bugfix for APT with MDNs (#734)
• bugfix: atomic SNPE-C now allows any kind of proposal (#732)
• bugfix for SNPE with implicit prior on GPU (#730)
• SNPE-A has force_first_round_loss=True as default (#729)