bayespy 0.6.2

Description:

bayespy 0.6.2

BayesPy provides tools for Bayesian inference with Python. The user
constructs a model as a Bayesian network, observes data and runs
posterior inference. The goal is to provide a tool which is
efficient, flexible and extendable enough for expert use but also
accessible for more casual users.
Currently, only variational Bayesian inference for
conjugate-exponential family (variational message passing) has been
implemented. Future work includes variational approximations for
other types of distributions and possibly other approximate inference
methods such as expectation propagation, Laplace approximations,
Markov chain Monte Carlo (MCMC) and other methods. Contributions are
welcome.

Project information
Copyright (C) 2011-2017 Jaakko Luttinen and other contributors (see below)
BayesPy including the documentation is licensed under the MIT License. See
LICENSE file for a text of the license or visit
http://opensource.org/licenses/MIT.


Latest release


Documentation
http://bayespy.org

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

Bug reports
https://github.com/bayespy/bayespy/issues

Author
Jaakko Luttinen [email protected]

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Mailing list
[email protected]




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master (stable)




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Contributors
The list of contributors:

Jaakko Luttinen
Hannu Hartikainen
Deebul Nair
Christopher Cramer
Till Hoffmann

Each file or the git log can be used for more detailed information.