A practical tutorial on Variational Bayes
It serves as an accessible resource for data analysis practitioners, but it is incremental as it focuses on tutorial content without introducing new methods.
This tutorial provides a practical introduction to Variational Bayes (VB) methods, enabling readers to quickly derive and implement VB algorithms for Bayesian inference in data analysis problems, with an accompanying Matlab software package available.
This tutorial gives a quick introduction to Variational Bayes (VB), also called Variational Inference or Variational Approximation, from a practical point of view. The paper covers a range of commonly used VB methods and an attempt is made to keep the materials accessible to the wide community of data analysis practitioners. The aim is that the reader can quickly derive and implement their first VB algorithm for Bayesian inference with their data analysis problem. An end-user software package in Matlab together with the documentation can be found at https://vbayeslab.github.io/VBLabDocs/