Overview
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Explore the connections between optimal transport theory and high-dimensional probability in this 57-minute lecture by Yair Shenfeld from Brown University. Delve into functional inequalities, including the log-Sobolev inequality and Talagrand's inequality, and examine their role in the convergence of flows. Investigate the concepts of displacement convexity and logconcavity of probability measures, gaining insights into the interplay between optimal transport techniques and probabilistic phenomena in high-dimensional spaces.
Syllabus
Yair Shenfeld Optimal transport and high-dimensional probability
Taught by
Institute for Mathematical Sciences
Reviews
4.0 rating, based on 1 Class Central review
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It was bravo and super clear explanation of Optimal Transport and how it connects to high-dimensional probability. The speaker breaks down complex ideas like Wasserstein distance and measure concentration in a way that actually makes sense. It was really insightful and well presented I learned a lot from it. I highly recommended for anyone studying probability, data science, or machine learning