Variable elimination algorithm in Bayesian networks: An updated version
Source of Publication
AIP Conference Proceedings
Given a Bayesian network relative to a set I of discrete random variables, we are interested in computing the probability distribution Pr(S), where the target S is a subset of I. The general idea of the Variable Elimination algorithm is to manage the successions of summations on all random variables out of the target. We propose a variation of the Variable Elimination algorithm that will make intermediate computation written as conditional probabilities and not simple potentials. This has an advantage in storing the joint probability as a product of conditions probabilities thus less constraining.
Smail, Linda, "Variable elimination algorithm in Bayesian networks: An updated version" (2023). All Works. 6251.
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