Learning tractable NAT-modeled Bayesian networks

DOI10.1007/s10472-021-09748-0zbMath1494.68233OpenAlexW3164395633MaRDI QIDQ825002

Yang Xiang, Qian Wang

Publication date: 17 December 2021

Published in: Annals of Mathematics and Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10472-021-09748-0

zbMATH Keywords

Bayesian networksprobabilistic inferencemachine learningcausal independence modelslocal structures

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Reasoning under uncertainty in the context of artificial intelligence (68T37) Probabilistic graphical models (62H22)

Cites Work

• Unnamed Item
• An intercausal cancellation model for Bayesian-network engineering
• Modeling by shortest data description
• Direct causal structure extraction from pairwise interaction patterns in NAT modeling Bayesian networks
• Learning Bayesian networks: The combination of knowledge and statistical data
• Non-impeding noisy-AND tree causal models over multi-valued variables
• An Approximate Tensor-Based Inference Method Applied to the Game of Minesweeper
• Metaheuristics for Score-and-Search Bayesian Network Structure Learning

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