Description:

BayesPy provides tools for variational Bayesian inference in Python. The model is constructed as a Bayesian network. The aim is to provide a tool which is efficient, flexible and extendable enough for expert use but also accessible for more casual users.

• Documentation: http://bayespy.org

• Repository: https://github.com/bayespy/bayespy

Changes to previous version:

• added all common distributions: Poisson, beta, multinomial, Bernoulli, categorical, etc

• added Gaussian arrays (not just scalars or vectors)

• added Gaussian Markov chains with time-varying or swithing dynamics

• added discrete Markov chains (enabling hidden Markov models)

• added deterministic gating node

• added deterministic general sum-product node

• added parameter expansion

• added new plotting functions: pdf, Hinton diagram

• added monitoring of posterior distributions during iteration

• improved documentation

BibTeX Entry: Download

Supported Operating Systems: Platform Independent

Data Formats: Hdf, Csv

Tags: Variational Inference, Bayesian Inference

Archive: download here

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