v1.0.4

What's Changed

• Update actions/download-artifact (https://github.com/advisories/GHSA-… by @pipme in #147
• Update numpy and cma versions. by @pipme in #146

Full Changelog: v1.0.3...v1.0.4

What's Changed

• Update actions/download-artifact (https://github.com/advisories/GHSA-… by @pipme in #147
• Update numpy and cma versions. by @pipme in #146
• Update upload-artifact. by @pipme in #148
• Chore(deps): Bump pypa/gh-action-pypi-publish from 1.6.4 to 1.10.2 by @dependabot in #151
• Chore(deps): Bump actions/checkout from 3 to 4 by @dependabot in #150
• Chore(deps): Bump actions/setup-python from 4 to 5 by @dependabot in #149

New Contributors

• @dependabot made their first contribution in #151

Full Changelog: v1.0.3...v1.0.4

v1.0.3

What's Changed

• Patch for numpy 2.0.0. #145

Full Changelog: v1.0.2...v1.0.3

v1.0.2

What's Changed

• Developer instructions by @Bobby-Huggins in #141
• JOSS-accepted by @Bobby-Huggins in #142
• Fix ParameterTransformer. by @pipme in #143
• Bug fixes. by @pipme in #144

Full Changelog: v1.0.1...v1.0.2

v1.0.1

What's Changed

• Update references by @Bobby-Huggins in #134
• Minor fixes from JoSS review + static linting by @Bobby-Huggins and @pipme in #140

Full Changelog: v1.0.0...v1.0.1

v1.0.0

First full-version release of PyVBMC, a Python package for efficient Bayesian inference. Full documentation is available at https://acerbilab.github.io/pyvbmc/. Feedback is welcome, see troubleshooting and contact. The same packaged version is also available at https://pypi.org/project/PyVBMC/#history.
Additional details of the algorithm can be found in the two Variational Bayesian Monte Carlo papers published at NeurIPS in 2018 and 2020.
A MATLAB implementation is also available at the acerbilab/VBMC repository.

What's Changed

• feat: PyVBMC now accepts optional prior distributions. See example 5 for more details.
• fix: eliminate log warning by setting KL divergences to inf. by @pipme in #125
• Other minor/cosmetic changes.

Full Changelog: v0.9.1...v1.0.0

PyVBMC Public Beta

Fixes a potential IndexError when using Numpy version 1.23 and newer.

PyVBMC Public Beta

Initial public beta version of PyVBMC, a Python package for efficient Bayesian inference. Full documentation is available at https://acerbilab.github.io/pyvbmc/. Feedback is welcome, see troubleshooting and contact. The same packaged version is also available at https://pypi.org/project/PyVBMC/#history.
Additional details of the algorithm can be found in the two Variational Bayesian Monte Carlo papers published at NeurIPS in 2018 and 2020.
A MATLAB implementation is also available at the acerbilab/VBMC repository.