Exploiting local and repeated structure in dynamic Bayesian networks

DOI10.1016/j.artint.2015.12.001zbMath1351.68288OpenAlexW2257860769MaRDI QIDQ2634474

Guy Van den Broeck, Wannes Meert, Luc De Raedt, Jonas Vlasselaer

Publication date: 9 February 2016

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.artint.2015.12.001

zbMATH Keywords

probabilistic inferencedynamic Bayesian networksprobabilistic graphical modelsknowledge compilation

Mathematics Subject Classification ID

Reasoning under uncertainty in the context of artificial intelligence (68T37)

Related Items (4)

Inferring range of information diffusion based on historical frequent items ⋮ \(T_{\mathcal{P}}\)-compilation for inference in probabilistic logic programs ⋮ Asymmetric hidden Markov models ⋮ Generating random instances of weighted model counting. An empirical analysis with varying primal treewidth

Cites Work

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• On probabilistic inference by weighted model counting
• Compiling relational Bayesian networks for exact inference
• Modeling and Reasoning with Bayesian Networks
• Inference and learning in probabilistic logic programs using weighted Boolean formulas
• Constant-space reasoning in dynamic Bayesian networks

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