Time: 3:00 p.m. - 4:00 p.m.

Location: Centergy Building 5126. The associated zoom link is: https://gatech.zoom.us/j/96519281318

Speaker: Lars Ruthotto

Speakers' Title: Emory University Winship Distinguished Research Associate Professor of Mathematics and Computer Science

Seminar Title: Differential Equations for Continuous-Time Deep Learning

Abstract: In this talk, we introduce and survey continuous-time deep learning approaches based on neural ordinary differential equations (neural ODEs) arising in supervised learning, generative modeling, and numerical solution of high-dimensional optimal control problems. We will highlight theoretical advantages and numerical benefits of neural ODEs in deep learning and their use to solve otherwise intractable PDE problems.

Bio: Lars Ruthotto am an applied mathematician developing computational methods for machine learning and inverse problems. He is a Winship Distinguished Research Associate Professor in the Department of Mathematics and the Department of Computer Science at Emory University and a member of Emory’s Scientific Computing Group. Ruthotto lead the Emory REU/RET site for Computational Mathematics for Data Science. Prior to joining Emory, he was a postdoc at the University of British Columbia, and held Ph.D positions at the University of Lübeck and the University of Münster.