Bayesian inference

Maria Fernanda Gil

Bernardo Flores

Prof. Richard Nickl | Bayesian Inference for Non-linear Inverse Problems

Andrew Gelman: Hierarchical modeling and prior information: an example from toxicology

[ИАД, осень 2025] Байесовский выбор моделей. Лекция 5: Обоснованность, связь со стат. значимостью

[IAD, Fall 2025] Bayesian Model Selection. Lecture 5: Validity, Connection to Statistical Significance

Inferencia Bayesiana Estructura Poblacional - Veronica Lia

Bayesian Inference Population Structure - Veronica Lia

[ИАД, осень 2025] Байесовский выбор моделей. Лекция 1: Введение

[IAD, Fall 2025] Bayesian Model Selection. Lecture 1: Introduction

La Extraña Matemática Que Predice (Casi) Todo

The Strange Mathematics That Predicts (Almost) Everything

Initiation à la statistique bayésienne

Introduction to Bayesian Statistics

Continuous version of Bayes rule

The basic idea of Bayesian Network

Science, Bayes & NL

Centered versus non-centered hierarchical models

Bayes theorem, the geometry of changing beliefs

What are divergent iterations and what to do about them?

How to write your first Stan program

Introducing Bayes factors and marginal likelihoods

Why we typically use dependent sampling to sample from the posterior

What is a posterior predictive check and why is it useful?

The problems with using simple Monte Carlo to determine the marginal likelihood

The intuition behind the Hamiltonian Monte Carlo algorithm

How to derive a Gibbs sampling routine in general

Estimating the posterior predictive distribution by sampling

Constrained parameters? Use Metropolis-Hastings

An introduction to the Random Walk Metropolis algorithm

An introduction to reference priors

An introduction to Jeffreys priors - 2

The syllabus covered by the book and YouTube course

Théorème de Bayes

Bayes' Theorem

The Bayesian Trap