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 foundational questions. Topics include probabilistic graphical models, variational inference, MCMC methods, optimal transport, tools from statistical physics, and generative modeling using neural networks.
Lectures: Thursdays at noon-1:40pm ET - 60 Fifth Ave Room 150
Join via Zoom: [<https://nyu.zoom.us/j/99629097105>](<https://nyu.zoom.us/j/99629097105>)
Recitations: Mondays at 11:15am-12:05pm ET - 60 Fifth Ave Room 150
Join via Zoom: [<https://nyu.zoom.us/j/5159082475>](<https://nyu.zoom.us/j/5159082475>)
Campuswire : https://campuswire.com/p/G82B7410D (code: 3320)
Brightspace (for assignments and grades): https://brightspace.nyu.edu/d2l/home/224620
Instructor Office Hour: Fridays 3pm - 4pm - 60 Fifth Ave Room 612
TA Office Hour: Wednesdays 4pm-5pm ET - 60 Fifth Ave Room 763
Project Groups: https://docs.google.com/spreadsheets/d/135OozSIybrW0kEfrO4gZ6BVzJo6gF_z-aMCRSwrYwNQ/edit?usp=sharing
Lecture Instructor:
TA: