Bayesian Model Selection (Fall, 2026)

This course offers a mathematically rigorous introduction to Bayesian statistics and its related fields. We cover the concepts of prior distributions and evidence, the EM algorithm, MCMC sampling, and Bayesian optimization, along with mathematical foundations.

Course instructors

• Alexander Aduenko
• Konstantin Yakovlev Konstantin-Iakovlev

Course Materials & Plan

Week	Date	Topic
1		Introduction

Home Assignments

References and Related Literature

1. Barber D. Bayesian reasoning and machine learning. – Cambridge, UK : Cambridge University Press, 2012. – Т. 1.

2. Sinho Chewi (2026). Log-Concave Sampling: pdf.