The aim of this graduate-level course is to describe the mathematical aspects of modeling high-dimensional data, with an emphasis on computational and statistical theoretical questions. Topics include probabilistic graphical models, variational inference, MCMC methods, optimal transport, and tools from statistical physics.
Lectures: Tuesdays at 4.55pm-6.35pm ET - Blended (Online & In-Person [19W4, Room 101]) - Zoom
Recitations: Either one of the two
Campuswire: Link
Office Hours: Tuesdays at 9:30am-11am ET - Zoom
Lecture Instructors:
TAs: