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Variational Bayes: A Gentle Introduction

This repository contains the Jupyter Notebook for the talk Variational Bayes: A Gentle Introduction

The notebook on variational inference with PyMC3 is based on this blogpost

The slides for the talk can be found here

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Variational inference is a technique for estimating Bayesian models that provides similar precision to MCMC at a greater speed, and is one of the main areas of current research in Bayesian computation. In this introductory talk, we take a look at the theory behind the variational approach and some of the most common methods (e.g. mean field, stoch…

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