Project details for BayesPy

Logo BayesPy 0.3.2

by jluttine - March 16, 2015, 11:58:37 CET [ Project Homepage BibTeX Download ]

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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.

Changes to previous version:
  • Concatenate node added
  • Unit tests for plotting fixed
BibTeX Entry: Download
URL: Project Homepage
Supported Operating Systems: Platform Independent
Data Formats: Hdf, Csv
Tags: Variational Inference, Bayesian Inference
Archive: download here

Other available revisons

Version Changelog Date
  • Concatenate node added
  • Unit tests for plotting fixed
March 16, 2015, 11:58:37
  • Gaussian mixture 2D plotting improvements
  • Covariance matrix sampling improvements
  • Minor documentation fixes
March 12, 2015, 14:32:34
  • Add gradient-based optimization methods (Riemannian/natural gradient or normal)
  • Add collapsed inference
  • Add the pattern search method
  • Add deterministic annealing
  • Add stochastic variational inference
  • Add optional input signals to Gaussian Markov chains
  • Add unit tests for plotting functions (by Hannu Hartikainen)
  • Add printing support to nodes
  • Drop Python 3.2 support
March 5, 2015, 09:26:26
  • Fix matplotlib compatibility broken by recent changes in matplotlib>=1.4.0
  • Add random sampling for Binomial and Bernoulli nodes
  • Fix minor bugs, for instance, in plot module
December 3, 2014, 14:51:10
  • Fix normalization of categorical Markov chain probabilities (fixes HMM demo)
  • Fix initialization from parameter values
November 1, 2014, 11:06:01
  • Add workaround for matplotlib 1.4.0 bug related to interactive mode which affected monitoring

  • Fix bugs in Hinton diagrams for Gaussian variables

September 30, 2014, 16:35:11
  • 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

August 14, 2014, 17:24:22

Initial Announcement on

September 25, 2013, 16:10:58


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