Lecture: Advanced Machine Learning: Deep Generative Models

This course (CIT4230003) builds upon the knowledge you gained in the lecture Machine Learning (IN2064). In this course, we will cover a wide range of recent deep generative models and explore more advanced learning principles that serve as the foundation for current state-of-the-art models like DALL-E.

Information

• Lecture/Exercise: tbd
• Required knowledge: Content of our Machine Learning lecture

All announcements will be made on the Piazza forum, which can be accessed via the link on the course's moodle page.
Please do not send any questions about organizational matters via e-mail.
If you have problems accessing the Moodle course, contact l.schwinn [at] tum.de .

Tentative list of topics

1. Normalizing flows
2. Variational inference and variational autoencoders
3. Generative adversarial networks
4. Generative diffusion and score-based methods