TY - CHAP
T1 - Statistical Optimal Transport
T2 - École d’Été de Probabilités de Saint-Flour XLIX-2019
AU - Chewi, Sinho
AU - Niles-Weed, Jonathan
AU - Rigollet, Philippe
N1 - Publisher Copyright:
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - This monograph aims to offer a concise introduction to optimal transport, quickly transitioning to its applications in statistics and machine learning. It is primarily tailored for students and researchers in these fields, yet it remains accessible to a broader audience of applied mathematicians and computer scientists. Each chapter is complemented with exercises for the reader to test their understanding. As such, this monograph is suitable for a graduate course on the topic of statistical optimal transport.
AB - This monograph aims to offer a concise introduction to optimal transport, quickly transitioning to its applications in statistics and machine learning. It is primarily tailored for students and researchers in these fields, yet it remains accessible to a broader audience of applied mathematicians and computer scientists. Each chapter is complemented with exercises for the reader to test their understanding. As such, this monograph is suitable for a graduate course on the topic of statistical optimal transport.
KW - Entropic Optimal Transport
KW - Optimal Transport
KW - Transport Map Estimation
KW - Wasserstein Barycenters
KW - Wasserstein Gradient Flows
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U2 - 10.1007/978-3-031-85160-5
DO - 10.1007/978-3-031-85160-5
M3 - Chapter
AN - SCOPUS:105004900146
T3 - Lecture Notes in Mathematics
SP - 1
EP - 256
BT - Lecture Notes in Mathematics
PB - Springer Science and Business Media Deutschland GmbH
ER -