Also available on zoom- https://umd.zoom.us/j/
After briefly touring the increasing interplay between computer graphics and machine learning, I will highlight one recent path of growing intersection between these two communities: the development and application of differentiable simulators.
Here, I make the specific claim that expertise and advances development in the computational physics, statistical and numerical methods, and — ultimately — computer graphics communities can lead to powerful inductive biases in physics-oriented learning tasks. I will survey the many reasons — motivated in part by a recent case study — for my excitement in maintaining and a research agenda that combines computer graphics-oriented methodologies to physics-based machine learning.
Derek Nowrouzezahrai is an Associate Professor at McGill University and a Core Faculty Member of the Quebec Institute for Artificial Intelligence (Mila). He Directs the McGill Graphics Lab and McGill University's Centre for Intelligent Machines, a grouping of over a dozen labs in the Faculty of Engineering and the Faculty of Science. He held a Post-Doctoral position at Disney Research Zurich after completing his graduate work at the University of Toronto.