Past talk · AI/ML Seminar Series
Deep Generative Models in Infinite-Dimensional Spaces
PhD Student, Department of Computer Science, UC Irvine
- Date & time
- Monday, January 29, 2024 · 1:00 PM
- Location
- Donald Bren Hall 4011
Abstract
Deep generative models have seen a meteoric rise in capabilities across a wide array of domains, ranging from natural language and vision to scientific applications such as precipitation forecasting and molecular generation. However, a number of important applications focus on data which is inherently infinite-dimensional, such as time-series, solutions to partial differential equations, and audio signals. This relatively under-explored class of problems poses unique theoretical and practical challenges for generative modeling. In this talk, we will explore recent developments for infinite-dimensional generative models, with a focus on diffusion-based methodologies.
About the speaker
Gavin Kerrigan is a PhD candidate in the Department of Computer Science at UC Irvine, where he is advised by Padhraic Smyth. Prior to joining UC Irvine, he obtained a BSc in mathematics from the Schreyer Honors College at Penn State University. His research is focused on deep generative models and their application to scientific domains. He was awarded an HPI fellowship and currently serves as a workflow chair for AISTATS.