A practical tutorial on Variational Bayes

TL;DR

This tutorial provides an accessible introduction to Variational Bayes, guiding practitioners on deriving and implementing VB algorithms for Bayesian inference, supported by practical software tools.

Contribution

It offers a practical, beginner-friendly overview of Variational Bayes methods along with a MATLAB software package for implementation.

Findings

Accessible overview of VB methods

Practical algorithms for Bayesian inference

Supporting software package in MATLAB

Abstract

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/