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Research questionHow can multiple Bayesian networks preserve shared dependencies while keeping treewidth low enough for tractable inference?Combining Bayesian networks can preserve too many dependencies, producing high-treewidth structures that make inference difficult to scale. Pruning edges improves tractability but may discard dependencies or retain structures specific to noisy inputs.
AI
Machine Learning
Neural and Evolutionary Computing
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Statistical Machine Learning
Latest papersRecent research connected to this question, newest first.Genetic Algorithms for Tractable Bayesian Network Fusion via Pre-Fusion Edge PruningThe source studies consensus fusion that prioritizes shared structures while enforcing treewidth limits. It reports synthetic and real-world experiments comparing genetic algorithms with adapted methods and greedy baselines; the evidence is limited to these evaluations.research paper · Sep 3, 2026
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