DS-GA 1005 - Fall 2023

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.

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