https://openalex.org/T11303
This cluster of papers focuses on the learning, inference, and applications of Bayesian networks and related probabilistic graphical models. It covers topics such as causal inference, graphical model structure learning, Markov logic networks, and the use of imprecise probabilities in modeling. The papers also discuss various algorithms for probabilistic learning and highlight the applications of Bayesian networks in diverse fields such as ecology, healthcare, and decision making under uncertainty.
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rdfs:label "Learning and Inference in Bayesian Networks"@en ;
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skos:definition "This cluster of papers focuses on the learning, inference, and applications of Bayesian networks and related probabilistic graphical models. It covers topics such as causal inference, graphical model structure learning, Markov logic networks, and the use of imprecise probabilities in modeling. The papers also discuss various algorithms for probabilistic learning and highlight the applications of Bayesian networks in diverse fields such as ecology, healthcare, and decision making under uncertainty."@en ;
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skos:prefLabel "Learning and Inference in Bayesian Networks"@en ;
openalex:cited_by_count 979219 ;
openalex:works_count 43209 .