Online Course Catalog

This course develops the foundations of generative models, covering the four main pillars: variational inference (VAE), diffusion models (Diffusion), generative adversarial networks (GAN), and normalizing flows (Flow). Although mostly mathematical, the treatment of topics will be from first principles, often revisiting core undergraduate material (in linear algebra, probability, optimization), and visualizing them in the context of neural networks. Each topic will close with recent research papers and their corresponding applications.

4 hours

Undergraduate degree.

• Electrical and Computer Engineering