Optimal Transport: Theory and Applications

Related lectures (30)

Page 3 of 3

Explores the lower bound on total variation distance in Markov chains and its implications on mixing time.

Explores functors, natural transformations, and the theory of groups, emphasizing the importance of comparisons and structure preservation.

Covers the definition of the center of a function using finite differences and provides step-by-step proofs.

Explores optimal transport theory, transport maps, entropy, and their practical implications in mathematical optimization.

Explores fundamental groups, homotopy classes, and coverings in connected manifolds.

Explores modular arithmetic, emphasizing inverses and equations in Z/mZ, with practical examples and exercises.

Introduces Coq, covering defining propositions, proving theorems, and using tactics.

Explores fundamental solutions in partial differential equations, highlighting their significance in mathematical applications.

Explores convex functions, global minima, and their relationship with differentiability.

Covers the basic theory for continuous time Markov chains and discusses communication, hitting probabilities, recurrence, and transience.