2023 IAIFI Summer School

1. Differential Equations and Generative Models

(Author: Miranda Cheng)

Useful materials

Tutorial

(Author: Anindita Maiti)

• Tutorial 1: KL Divergence
• Tutorial 2: Neural ODEs (resource - Neural Ordinary Differential Equations by Chen et. al.)
• Tutorial 3: Normalizing Flows (resource - Variational Inference with Normalizing Flows by Rezende et. al.)

2. Statistical Physics and Geometry of Overparameterization

(Author: Pankaj Mehta)

Useful materials

Tutorial

(Author: Di Luo)

3. Generative modeling, with connection to and applications in physics

(Author: Siddharth Mishra-Sharma)

• Preliminary slides: https://smsharma.github.io/iaifi-summer-school-2023/

Useful materials

Introductory posts:

• Musings on typicality by Sander Dieleman
• A Path to the Variational Diffusion Loss by Alex Alemi
• Flow-based Deep Generative Models by Lilian Weng
• Perspectives on diffusion by Sander Dieleman

Code:

• Minified generative models: A repository with minimal/pedagogical implementations of some generative models.

Tutorial

(Author: Carol Cuesta-Lazaro)

4. Astrostatistics

(Author: Joshua Speagle)

Useful materials

Tutorial

(Author: Alex Gagliano)

5. Incorporating Symmetry into Deep Dynamics Models

(Author: Robin Walters)

Useful materials

Tutorial

(Author: Ray Wang)