## Applied Mathematics

•  Yang Wang, Hong Kong University of Science and Technology
•  10/29/2020
•  4:30 AM - 5:30 AM
•  Olga Turanova (turanova@msu.edu)

(Note the unusual time: 4:30pm Shanghai, 10:30am Paris.)  Generative Adversarial Nets (GAN) have been one of the most exciting developments in machine learning and AI. But training of GAN is highly nontrivial. In this talk I will give an introduction to GAN, and propose a framework to learn deep generative models via Variational Gradient Flow (Vgrow) on probability measure spaces. Connections of our proposed VGrow method with other popular methods, such as VAE, GAN and flow-based methods, have been established in this framework, gaining new insights of deep generative learning.

## Contact

Department of Mathematics
Michigan State University