Introduction to Generative Models

Catalog description

An in-depth introduction to deep generative models. This course covers the mathematical foundations of generative models and their implementation as deep neural networks. Topics include diffusion models, variational autoencoders, generative adversarial networks, and network architectures for generation. These topics will be discussed in the context of applications in computer vision and natural language processing.