A new release of pymc-extras is now available!
Release Information
Version: v0.13.0
Repository: pymc-devs/pymc-extras
Release Page: Release v0.13.0 Β· pymc-devs/pymc-extras Β· GitHub
Note: It may take some time for the release to appear on PyPI and conda-forge.
Release Notes
Whatβs Changed
Major Changes
Allow closed form marginalization and implement conditional model transform by @ricardoV94 in #688
Compatibility with PyTensor v3.1 and PyMC v6.1 by @ricardoV94 in #708
New Features
Make basic INLA interface and simple marginalisation routine by @Michal-Novomestsky in #533
Implement time-varying P DiscreteMarkovChain and marginalized conditional/recover by @zaxtax in #693
Build autoguide in unconstrained space and add full and low rank multivariate guides by @ricardoV94 in #701
Full Changelog: Comparing v0.12.1...v0.13.0 Β· pymc-devs/pymc-extras Β· GitHub
This post was automatically generated from the GitHub release.
| # | ΠΠ°ΠΈΠΌΠ΅Π½ΠΎΠ²Π°Π½ΠΈΠ΅ Π½ΠΎΠ²ΠΎΡΡΠΈ | Π’ΠΎΠ½Π°Π»ΡΠ½ΠΎΡΡΡ | ΠΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠ²Π½ΠΎΡΡΡ | ΠΠ°ΡΠ° ΠΏΡΠ±Π»ΠΈΠΊΠ°ΡΠΈΠΈ |
|---|---|---|---|---|
| 1 | π Release pymc-extras v0.14.0 | 0 | 19.63 | 28-07-2026 |
| 2 | π Release pymc-extras v0.13.1 | 0 | 19.63 | 19-07-2026 |
| 3 | π Release v6.2.0 | 0 | 18.52 | 23-07-2026 |
| 4 | Hidden Markov Models in PyMC: marginalize and recover a DiscreteMarkovChain | 0 | 4.78 | 13-07-2026 |
| 5 | Pymc_forecast β a new Bayesian time-series forecasting toolkit for PyMC | 0 | 19.35 | 17-07-2026 |
| 6 | New contributor looking to get started β background in ML/RAG research | 0 | 10.42 | 23-07-2026 |
| 7 | Regarding GSOC 2027 and PyMC projects | 0 | 7.73 | 28-07-2026 |
| 8 | Hierarchical model with copula on GPU: NumPyro or nutpie using PyMC 5.19? | 0 | 9.57 | 09-07-2026 |
| 9 | Arviz Issues following Tutorials | 0 | 7.44 | 21-07-2026 |
| 10 | TypeError: Real.grad illegally returned an integer-valued variable - when pm.sample | 0 | 7.04 | 12-07-2026 |