# Segregated Graphs and Marginals of Chain Graph Models

@inproceedings{Shpitser2015SegregatedGA, title={Segregated Graphs and Marginals of Chain Graph Models}, author={Ilya Shpitser}, booktitle={NIPS}, year={2015} }

Bayesian networks are a popular representation of asymmetric (for example causal) relationships between random variables. Markov random fields (MRFs) are a complementary model of symmetric relationships used in computer vision, spatial modeling, and social and gene expression networks. A chain graph model under the Lauritzen-Wermuth-Frydenberg interpretation (hereafter a chain graph model) generalizes both Bayesian networks and MRFs, and can represent asymmetric and symmetric relationships…

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