Variational Message Passing

Winn, J. M., & Bishop, C. M. (2005). Variational Message Passing. Journal of Machine Learning Research.

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2005

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• Variational Message Passing
  • It is the compilation of that identity into local messages for conjugate-exponential Bayesian networks: parent-to-child messages carry expected sufficient statistics, child-to-parent messages carry contributions to natural parameters, and a node's updated variational distribution is formed from the incoming contributions

    This sourceThe paper names exactly this class - hidden Markov models, Kalman filters, factor analysers, principal component analysers, and mixtures and hierarchical mixtures of these - as special cases of its conjugate-exponential architecture (section 4 sets out the allowable building blocks); the Gaussian mixture is the case worked through in full.

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