Mathematical Foundations of Machine Learning II: Generative Learning

In this lecture, we continue with the mathematical description of machine learning with a focus on generative learning.

We will first complete some topics like universal approximation properties of deep neural networks not covered in part one and then move on to generative adversarial learning and invertible neural networks / normalizing flows. The first lecture takes place on Monday 16th of October.

The lecture series is based on Mathematical Foundations of Machine Learning I.