DS-GA 1005 - Fall 2025

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, and generative modeling using neural networks.

Logistics

• Lectures: Mondays at 10:15-12:15am ET - 60 5th Ave Room 150
• Recitations: Wednesdays at 11:15am-12:05pm ET - 60 Fifth Ave Room 150
• Brightspace (for assignments and grades): https://brightspace.nyu.edu/d2l/home/498277
• Instructor Office Hour: Mondays 12:10pm - 13:10pm - 60 Fifth Ave Room 611
• TA Office Hour: Wednesdays 12:10pm - 13:10pm - 60 Fifth Ave Room 242

Instructors

Lecture Instructor:

• Yoav Wald ([email protected])

TA:

• Xiang Gao ([email protected])

General information

• Syllabus
• Grading
• Bibliography
• Courses on Inference we like

Final Projects

Schedule