MATH858U
Selected Topics in Analysis; Mathematical Methods in Machine Learning
This course introduces students to the advanced mathematical concepts arising in the context of machine learning. The topics that we will cover include: universal approximation theorems and expressivity theory, geometric deep learning and graph neural networks, optimal transport theory and diffusion models.
Sister Courses: MATH858A, MATH858B, MATH858C, MATH858D, MATH858E, MATH858F, MATH858G, MATH858I, MATH858J, MATH858K, MATH858L, MATH858M, MATH858N, MATH858P, MATH858Q, MATH858R, MATH858S, MATH858T, MATH858V, MATH858W, MATH858Y
Fall 2026
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