Statistical Foundations of Deep Generative Models

Generative AI has achieved remarkable performance in many domains, motivating theoretical work on its foundations. This talk examines deep generative models from a nonparametric distribution-estimation perspective, where the generator is parameterized by a deep neural network.

Lizhen Lin is a professor of statistics in the Department of Mathematics at the University of Maryland and director of the statistics program. Her expertise includes Bayesian modeling, high-dimensional theory, statistics on manifolds, network analysis, and foundations of deep neural network models.