A reconstruction algorithm for the essential graph

DOI10.1016/j.ijar.2008.09.001zbMath1191.68534OpenAlexW2129118887MaRDI QIDQ962864

Jiří Vomlel, Milan Studený

Publication date: 7 April 2010

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2008.09.001

zbMATH Keywords

chain graphBayesian network structureessential graphstandard imset

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (6)

A new prior for discrete DAG models with a restricted set of directions ⋮ Characteristic imsets for learning Bayesian network structure ⋮ On open questions in the geometric approach to structural learning Bayesian nets ⋮ A geometric view on learning Bayesian network structures ⋮ Structural Markov graph laws for Bayesian model uncertainty ⋮ Standard imsets for undirected and chain graphical models

Cites Work

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• Racing algorithms for conditional independence inference
• A characterization of Markov equivalence classes for acyclic digraphs
• Characterization of inclusion neighbourhood in terms of the essential graph
• A recovery algorithm for chain graphs
• On the Markov Equivalence of Chain Graphs, Undirected Graphs, and Acyclic Digraphs
• Probabilistic Networks and Expert Systems
• 10.1162/153244303321897717
• A Unified Approach to the Characterization of Equivalence Classes of DAGs, Chain Graphs with no Flags and Chain Graphs
• CHARACTERIZATION OF ESSENTIAL GRAPHS BY MEANS OF THE OPERATION OF LEGAL MERGING OF COMPONENTS

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