Optimal transport (OT) is a fundamental mathematical theory at the interface between optimization, partial differential equations and probability. It has recently emerged as an important tool to tackle a surprisingly large range of problems in data sciences, such as shape registration in medical imaging, structured prediction problems in supervised learning and training deep generative networks.
PEYRÉ Gabriel
Speakers
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SEBBOUH Othmane
PhD student
TRIGG Scott
Postdoctoral researcher