Variational Bayes Made Easy
Machine Learning
2023-07-11 v2 Artificial Intelligence
Machine Learning
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.
Cite
@article{arxiv.2304.14251,
title = {Variational Bayes Made Easy},
author = {Mohammad Emtiyaz Khan},
journal= {arXiv preprint arXiv:2304.14251},
year = {2023}
}