On conditional truncated densities Bayesian networks

DOI10.1016/j.ijar.2017.10.007zbMath1423.68379OpenAlexW2765292055MaRDI QIDQ1687280

Christophe Gonzales, Santiago Cortijo

Publication date: 22 December 2017

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

Full work available at URL: https://hal.sorbonne-universite.fr/hal-01626202/file/Cortijo_On_Conditional.pdf

zbMATH Keywords

inferenceBayesian networkcontinuous random variablemixed probability distribution

Mathematics Subject Classification ID

Analysis of algorithms and problem complexity (68Q25) Learning and adaptive systems in artificial intelligence (68T05) Reasoning under uncertainty in the context of artificial intelligence (68T37)

Uses Software

• UCI-ml

Cites Work

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• Mixtures of truncated basis functions
• Two issues in using mixtures of polynomials for inference in hybrid Bayesian networks
• Inference in hybrid Bayesian networks using mixtures of polynomials
• Approximate probability propagation with mixtures of truncated exponentials
• Graphical models for associations between variables, some of which are qualitative and some quantitative
• Binary join trees for computing marginals in the Shenoy-Shafer architecture
• Bucket elimination: A unifying framework for reasoning
• Lazy propagation: A junction tree inference algorithm based on lazy evaluation
• On probabilistic inference by weighted model counting
• Inference in hybrid Bayesian networks with mixtures of truncated exponentials
• A Re-definition of Mixtures of Polynomials for Inference in Hybrid Bayesian Networks
• Propagation of Probabilities, Means, and Variances in Mixed Graphical Association Models
• Monte Carlo sampling methods using Markov chains and their applications

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