mlsanityData to 7 Oct 2026

BayesPy: Variational Bayesian Inference in Python

arXiv 1410.0870 ↗First posted 3 Oct 2014stat.ML stat.COcited by 4

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Abstract (arXiv)

BayesPy is an open-source Python software package for performing variational Bayesian inference. It is based on the variational message passing framework and supports conjugate exponential family models. By removing the tedious task of implementing the variational Bayesian update equations, the user can construct models faster and in a less error-prone way. Simple syntax, flexible model construction and efficient inference make BayesPy suitable for both average and expert Bayesian users. It also supports some advanced methods such as stochastic and collapsed variational inference.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Oct 2014.

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4 papers.