Preliminary remark

These handouts have been created for my personal use. Some parts are copied or inspired from external sources and they are indicated in the documents. All mistakes are my own.

Variation Bayes

This document summarizes briefly the basic ideas of Variation Bayes Inference. (Created for my summer research project 2020).

Sampling Methods : MCMC, Metropolis Hasting and Gibbs sampling

Source of the image : Maxwell Joseph, Blog post

This document introduces briefly the main ideas of MCMC methods, explains one example which is the Metropolis-Hasting algorithm and Gibbs sampling for the multivariate case. (Created for my summer research project 2020. Might be completed)

Probability distributions

Source of the image : Twitter, Sacha schutz

This document aims to describe briefly different probability distributions (pdf, expectation, variance, support and use) in order to have an overview of what are common probability distributions, in which case they can be used and why, and to use them to create new probability distributions or new modelings. The main goal was to have a simple and personal visual paper of existing probability distributions. (To be completed)