Schedule


* = optional reading

Date Topic Readings / Videos Assignments
09 Apr

Introduction

11 Apr

Exercise 01

Assignment 0: Why Generative Models
16 Apr

Graphical Models & Monte Carlo Methods

reading
18 Apr

Exercise 02

Assignment 1: Probability Review
23 Apr

Partition Function & RBMs

reading
25 Apr

Exercise 03

Assignment 2: MCMC and Gibbs Sampling
30 Apr

Approximate Inference & VAEs

  • Selected resources
reading
02 May

Exercise 04

Assignment 3: Restricted Boltzmann Machines
07 May

Generative Adversarial Networks

  • Selected resources
reading
14 May

Evaluating Generative Models

  • Selected resources
reading
16 May

Exercise 05

Assignment 4: Variational Autoencoders
21 May

Autoregressive Models

  • Selected resources
reading
23 May

Exercise 06

Assignment 5: Generative Adversarial Networks
28 May

Normalizing Flows

  • Selected resources
reading
30 May

Exercise 07

Assignment 6: Autoregressive Language Modeling
04 Jun

Score-based Models

  • Selected resources
reading
06 Jun

Exercise 08

Assignment 7: Flows
11 Jun

Denoising Diffusion Models

  • Selected resources
reading
13 Jun

Exercise 09

Assignment 8: Score-Based Generative Models
18 Jun

Text-to-Image Generative Models

  • Selected resources
reading
20 Jun

Exercise 10

Assignment 9: Denoising Diffusion Models
25 Jun

Advanced VAEs and GANs

  • Selected resources
reading
27 Jun

Exercise 11

Assignment 10: Conditional & Guided Diffusion
02 Jul

Large Language Models

  • Selected resources
reading
04 Jul

Exercise 12

Assignment 11: Basic Audio Generation