Inference in hybrid Bayesian networks using mixtures of polynomials

DOI10.1016/j.ijar.2010.09.003zbMath1214.68404OpenAlexW2038282474MaRDI QIDQ541846

Prakash P. Shenoy, James C. West

Publication date: 8 June 2011

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

Full work available at URL: https://doi.org/10.1016/j.ijar.2010.09.003

zbMATH Keywords

mixtures of truncated exponentialshybrid Bayesian networksinference in hybrid Bayesian networksmixtures of polynomialsextended Shenoy-Shafer architectureShenoy-Shafer architecture

Mathematics Subject Classification ID

Bayesian inference (62F15) Reasoning under uncertainty in the context of artificial intelligence (68T37)

Related Items (17)

Hybrid semiparametric Bayesian networks ⋮ Influence diagrams for speed profile optimization ⋮ On conditional truncated densities Bayesian networks ⋮ Interval-based reasoning over continuous variables using independent component analysis and Bayesian networks ⋮ Semiparametric Bayesian networks ⋮ Mixtures of truncated basis functions ⋮ Modelling and inference with conditional Gaussian probabilistic decision graphs ⋮ Learning mixtures of polynomials of multidimensional probability densities from data using B-spline interpolation ⋮ Two issues in using mixtures of polynomials for inference in hybrid Bayesian networks ⋮ A Re-definition of Mixtures of Polynomials for Inference in Hybrid Bayesian Networks ⋮ Learning mixtures of truncated basis functions from data ⋮ Parameter learning in hybrid Bayesian networks using prior knowledge ⋮ A Framework for Solving Hybrid Influence Diagrams Containing Deterministic Conditional Distributions ⋮ Learning Conditional Distributions Using Mixtures of Truncated Basis Functions ⋮ A review of Gaussian Markov models for conditional independence ⋮ Advanced SMT techniques for weighted model integration ⋮ Directional naive Bayes classifiers

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