PyBNesian: An extensible python package for Bayesian networks

Bayesian networks are probabilistic graphical models that are commonly used to represent the uncertainty in data. The PyBNesian package provides an implementation for many different types of Bayesian network models and some variants, such as conditional Bayesian networks and dynamic Bayesian network...

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Bibliographic Details
Published in:Neurocomputing (Amsterdam) 2022-09, Vol.504, p.204-209
Main Authors: Atienza, David, Bielza, Concha, Larrañaga, Pedro
Format: Article
Language:English
Subjects:
Bayesian networks
Conditional independence
Dynamic models
Kernel density estimation
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Description
Summary:Bayesian networks are probabilistic graphical models that are commonly used to represent the uncertainty in data. The PyBNesian package provides an implementation for many different types of Bayesian network models and some variants, such as conditional Bayesian networks and dynamic Bayesian networks. In addition, the package can be easily extended with new components that can interoperate with those already implemented. Furthermore, the package also implements other related models such as kernel density estimation using OpenCL 1.2+ to enable GPU acceleration. PyBNesian is totally free and open-source under the MIT license.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2022.06.112