Variational message passing
Approximate interference technique in Bayesian networks / From Wikipedia, the free encyclopedia
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Variational message passing (VMP) is an approximate inference technique for continuous- or discrete-valued Bayesian networks, with conjugate-exponential parents, developed by John Winn. VMP was developed as a means of generalizing the approximate variational methods used by such techniques as latent Dirichlet allocation, and works by updating an approximate distribution at each node through messages in the node's Markov blanket.
This article may be too technical for most readers to understand. (February 2024) |