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pymc-devs/pymc: 4.0.0 beta 5

Authors: Wiecki, Thomas; Salvatier, John; Patil, Anand; Kochurov, Maxim; Vieira, Ricardo; Engels, Bill; Junpeng Lao; +23 Authors

pymc-devs/pymc: 4.0.0 beta 5

Abstract

What's Changed Generalize multinomial moment to arbitrary dimensions by @markvrma in https://github.com/pymc-devs/pymc/pull/5476 Remove sd optional kwarg from distributions by @purna135 in https://github.com/pymc-devs/pymc/pull/5583 Improve scoped models by @ferrine in https://github.com/pymc-devs/pymc/pull/5607 Add helper wrapper aound Interval transform by @ricardoV94 in https://github.com/pymc-devs/pymc/pull/5347 Rename logp_transform to _get_default_transform by @ricardoV94 in https://github.com/pymc-devs/pymc/pull/5612 Do not set RNG updates inplace in compile_pymc by @ricardoV94 in https://github.com/pymc-devs/pymc/pull/5615 Refine trigger filter for both PRs and pushes by @michaelosthege in https://github.com/pymc-devs/pymc/pull/5619 Update contributing guide with etiquette section by @michaelosthege in https://github.com/pymc-devs/pymc/pull/5611 Combine test workflows into one by @michaelosthege in https://github.com/pymc-devs/pymc/pull/5623 Raise ValueError if random variables are present in the logp graph by @ricardoV94 in https://github.com/pymc-devs/pymc/pull/5614 Run float32 jobs separately by @michaelosthege in https://github.com/pymc-devs/pymc/pull/5630 Bring back sampler argument target_accept by @aloctavodia in https://github.com/pymc-devs/pymc/pull/5622 Parametrize Binomial and Categorical distributions via logit_p by @purna135 in https://github.com/pymc-devs/pymc/pull/5637 Remove SGMCMC and fix flaky mypy results by @michaelosthege in https://github.com/pymc-devs/pymc/pull/5631 Full Changelog: https://github.com/pymc-devs/pymc/compare/v4.0.0b4...v4.0.0b5

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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