Bayesian Methods and Applications
A biweekly reading group on Bayesian inference, computation, and applications across the sciences.
Purpose
This reading group surveys modern Bayesian methods — from foundational theory to computational tools and applied case studies. The goal is to build fluency with Bayesian thinking and connect it to practical research problems across statistics, machine learning, and the sciences.
Structure
We follow a book-based format, working through Bayesian Data Analysis (Gelman et al., 3rd ed.) as the primary text, supplemented by research articles on specific topics. Each session covers 1–2 chapters or a paper. One member presents a summary, and the group works through exercises or discusses extensions.
Session 1 — June 2026
Upcoming — to be scheduled.