pyAgrum is a scientific C++ and Python open source library dedicated to Bayesian networks (BN) and other Probabilistic Graphical Models. 

Based on the C++ aGrUM library, it provides a high-level interface to the C++ part of aGrUM allowing to create, manage and perform efficient computations with Bayesian networks and others probabilistic graphical models : 

- Markov networks (MN), 
- influence diagrams (ID) and LIMIDs, credal networks (CN), 
- dynamic BN (dBN),
- probabilistic relational models (PRM).

Several topics have been added to pyAgrum (as pure python modules using pyAgrum) :

- Scikit-learn-compliant probabilistic classifiers based on Bayesian networks,
- Probabilistic causality (causal networks, do-calculus),
- dynamic Bayesian network,
- tools for explainability in Bayesian networks.

pyAgrum

Org chart

Teams

Offices