Schedule


* = optional reading

Date Topic Readings / Videos Assignments
05 Apr

Introduction

08 Apr

Exercise 01

Assignment 0: Why Generative Models
12 Apr

Graphical Models & Monte Carlo Methods

reading
19 Apr

Partition Function & RBMs

reading
22 Apr

Exercise 02

Assignment 1: Probability Review
26 Apr

Approximate Inference, DBNs & DBMs

reading
29 Apr

Exercise 03

Assignment 2: Monte Carlo & Gibbs Sampling
03 May

Deep Generative Networks & VAEs

reading
06 May

Exercise 04

Assignment 3: Restricted Boltzmann Machines
10 May

Advanced VAE Techniques

  • selected ressources
reading
13 May

Exercise 05

Assignment 4: Variational Autoencoders
17 May

Generative Adversarial Networks (GANs)

reading
20 May

Exercise 06

Assignment 5: Kernel Density Estimation
24 May

Generative Adversarial Networks (GANs) continued

reading
03 Jun

Exercise 07

Assignment 6/7: Generative Adversarial Networks
31 May

Autoregressive Networks (ARNs)

  • selected ressources
reading
07 Jun

Flow-Based Generative Models

  • selected ressources
reading
10 Jun

Exercise 10

Assignment 8: Autoregressive Models
14 Jun

Score-Based Models

  • selected ressources
reading
17 Jun

Exercise 11

Assignment 9: Flows
21 Jun

Denoising Diffusion Models

  • selected ressources
reading
24 Jun

Exercise 12

Assignment 10: VQ-VAEs
28 Jun

Differentiable Digital Signal Processing

  • selected ressources
reading
01 Jul

Exercise 13

Assignment 11: Diffusion Models
05 Jul

Cycle Consistency

  • selected ressources
reading