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Inference and Learning in discrete Bayesian Networks

Python library to perform Belief Propagation inference over discrete Bayesian Networks. Netwroks are defined by the user by means of tabular Conditional Probability Distributions (CPDs). Four python notebooks are included: two to describe how to use the library and run BP inference, and two to show how to learn the BNs CPDs with hidden observations using EM.

Slides are also provided!

Python 3.5 required!

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