Deep Generative Models

4 credits

This course will cover the fundamentals and state of the art of deep generative models, including large language models, diffusion models, generative adversarial networks, variational autoencoders, etc. Recommended prerequisites: Foundational knowledge in deep learning, probability, and statistics. Prerequisites: graduate standing.