About: Variational message passing

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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.

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  • 変分メッセージパッシング（へんぶんメッセージパッシング、英語: Variational message passing、VMP）はJohn Winnによって開発された、指数族のを用いた離散、連続ベイジアンネットワークを近似的に推論するための手法である。VMPはLatent Dirichlet allocation（LDA）などの手法で利用されるを一般化した手法であり、各々のノードの周辺分布を、その上に存在するメッセージを用いて逐次的に更新し、その近似解を求める。 (ja)
  • 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. (en)
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  • 変分メッセージパッシング（へんぶんメッセージパッシング、英語: Variational message passing、VMP）はJohn Winnによって開発された、指数族のを用いた離散、連続ベイジアンネットワークを近似的に推論するための手法である。VMPはLatent Dirichlet allocation（LDA）などの手法で利用されるを一般化した手法であり、各々のノードの周辺分布を、その上に存在するメッセージを用いて逐次的に更新し、その近似解を求める。 (ja)
  • 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. (en)
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  • 変分メッセージパッシング (ja)
  • Variational message passing (en)
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