A new release of pymc-extras is now available!
Release Information
- Version:
v0.16.0 - Repository: pymc-devs/pymc-extras
- Release Page: Release v0.16.0 · pymc-devs/pymc-extras · GitHub
- Note: It may take some time for the release to appear on PyPI and conda-forge.
Release Notes
What’s Changed
New Features 
- Fit BayesianETS through its innovations recursion instead of the Kalman filter by @jessegrabowski in #777
- Implement conditional recovery for Laplace-marginalized variables by @fonnesbeck in #790
- MLX MCLMC sampler by @jessegrabowski in #743
Bugfixes 
- Fix GeneralizedPoisson scalar draw by @ricardoV94 in #785
- Fix BetaNegativeBinomial generator parameterization by @fonnesbeck in #787
- Fix GEV log-CDF at the finite upper endpoint by @fonnesbeck in #788
- Preserve Prior core_dims during serialization by @fonnesbeck in #789
- Build the full-rank ADVI guide’s Cholesky factor with constant indices by @jessegrabowski in #795
Maintenance 
- Fix forecast with exogenous data on custom statespace models by @jessegrabowski in #794
- Run pathfinder on float32 models by @jessegrabowski in #813
- Bump pymc to 6.4 and pytensor to 3.3.6 by @jessegrabowski in #815
New Contributors
- @G26karthik made their first contribution in #802
Full Changelog: Comparing v0.15.1...v0.16.0 · pymc-devs/pymc-extras · GitHub
This post was automatically generated from the GitHub release.