STATISTICAL OPTIMAL TRANSPORT
This is a weekly reading seminar at NUS on Statistical Optimal Transport (following this monograph by Sinho Chewi, Jonathan Niles-Weed and Philippe Rigollet).
đź“‘Program:
Lecture 1: (Chapter 1) An introduction to Optimal Transport (Subhro Ghosh)
Lecture 2: (Chapter 1) Brenier's theorem and Kantorovich duality (Hoang Son Tran)
Lecture 3: (Chapter 2) The Wasserstein law of large numbers (Hoang Son Tran)
Lecture 4: (Chapter 2) Regularization of Wasserstein distances (Hoang Son Tran)
Lecture 5: (Chapter 3) Estimation of transport maps (Rathindra Karmakar)
Lecture 6: (Chapter 3) Estimation of transport maps (cont.) (Rathindra Karmakar)
Lecture 7: (Chapter 4) Entropic optimal transport (Xiaoyu Dong)
Lecture 8: (Chapter 4) Entropic optimal transport (cont.) (Xiaoyu Dong)
Lecture 9: (Chapter 5) The Riemannian structure on Wasserstein spaces (Hoang Son Tran)
Lecture 10: (Chapter 5) Otto calculus and Wasserstein gradient flows (Hoang Son Tran)
Lecture 11: (Chapter 5) Wasserstein-Fisher-Rao geometry and mean-field particle systems (Hoang Son Tran)
Lecture 12: (Chapter 6) Application of Wasserstein gradient flows in sampling (Rathindra Karmakar)
LOG-CONCAVE SAMPLING
This is a weekly online seminar on log-concave sampling (following this draft by Sinho Chewi).
đź“‘Program:
Lecture 1: (Chapter 1) Langevin diffusion via Markov semigroup theory (Hoang Son Tran)
Lecture 2: (Chapter 1) Geometry of Wasserstein space (Hoang Son Tran)
Lecture 3: (Chapter 1) Langevin diffusion as a Wasserstein gradient flow (Hoang Son Tran)