Variational Bayes Made Easy

Mohammad Emtiyaz Khan
4/27/2023
cs.LGcs.AIstat.ML

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Abstract

Variational Bayes is a popular method for approximate inference but its derivation can be cumbersome. To simplify the process, we give a 3-step recipe to identify the posterior form by explicitly looking for linearity with respect to expectations of well-known distributions. We can then directly write the update by simply ``reading-off'' the terms in front of those expectations. The recipe makes the derivation easier, faster, shorter, and more general.

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Cite this paper

@article{khan2023variational,
  title  = {Variational Bayes Made Easy},
  author = {Mohammad Emtiyaz Khan},
  year   = {2023},
  eprint = {2304.14251},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2304.14251v2}
}

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