Dynamic Importance Sampling in Bayesian Networks Based on Probability Trees

Dynamic Importance Sampling in Bayesian Networks Based on Probability Trees

In this paper we introduce a new dynamic importance sampling propagation algorithm for Bayesian networks. Importance sampling is based on using an auxiliary sampling distribution from which a set of con gurations of the variables in the network is drawn, and the performance of the algorithm depends...

書誌詳細
主要な著者:	Moral, Serafín, Salmerón Cerdán, Antonio
フォーマット:	info:eu-repo/semantics/article
言語:	English
出版事項:	2017
主題:	Bayesian networks Probability propagation Approximate algorithms Importance sampling Probability trees
オンライン･アクセス:	http://hdl.handle.net/10835/4893 https://doi.org/10.1016/j.ijar.2004.05.005

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