Practical Inference for Researchers in the Physical Sciences

by Francesca Capel (ODSL), Johannes Buchner (MPE)

Contents

• Getting started
  • Notebook
  • Questionaire
• Install
  • Option 1: on your own computer
  • Option 2: with Docker
  • Option 3: Binder
  • After installation
• Reading material
  • Books about Bayesian inference
  • Lectures
  • Research Papers on State-of-the-Art Methods

Lecture recordings

• (1/6) Bayesian inference workflow in astronomy and physics

• (2/6) Bayesian model comparison, curse of dimensionality, Importance Sampling

• (3/6) Markov Chain Monte Carlo (MCMC) and diagnostics

• (4/6) Hamiltonian Monte Carlo (HMC) by Dr. Francesca Capel

• (5/6) Nested Sampling from scratch - Practical Inference for Researchers in the Physical Sciences

• (6/6) State-of-the art in nested sampling and MCMC: literature review

Play all on youtube: https://www.youtube.com/watch?v=D2P6xBR_2bQ&list=PLXOfJVzebj3ZKhgW_0S987FC-lR2bGzjU

Important links

• Course web page: https://indico.ph.tum.de/event/6875/

• First week: Monte Carlo inference methods

  • Access from this page (see Getting started and Install pages)

  • Github repository

• Second week: Bayesian workflow course

  • Content

  • Github repository

To get access to the course, go to Getting started

Contributors

• Johannes Diehl

• Benedikt Wach

• Mikhail Mikhasenko

• Tatiana Nechaeva