swMATH ID: 38510
Software Authors: Doğu Kaan ERASLAN
Description: PyGModels: A Python package for exploring Probabilistic Graphical Models with Graph Theoretical Structures. Probabilistic Graphical Models (PGMs) are a marriage between “graphs” from graph theory and “probability” from statistics and probability theory. While PGMs are widely used in many elds, we noticed that most existing PGM libraries are implement in a way that doesn’t take full advantage of their graphical nature. PyGModels’ value proposition is that it faithfully im- plements the graphical nature of PGMs, thereby giving PyGModels’ instantiated objects both graph-theoretical and statistical properties, which allows users to explore and test inference algorithms that are rooted in graph theory or statistics. PyGModels also implements several algorithms of interest on Lauritzen-Wermuth-Frydenberg (LWF) chain graphs, also known as mixed graphs.
Homepage: https://www.theoj.org/joss-papers/joss.03115/10.21105.joss.03115.pdf
Dependencies: Python
Keywords: PyGModels; Python package; Probabilistic Graphical Models; PGM; Journal of Open Source Software; graph theory; probability theory
Related Software: Pgm; Pyfac; pyGM; Pgmpy; pomegranate; Python
Referenced in: 0 Publications

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