GT Transport optimal - EDP - Machine learning
Mind the reference measure of entropic OT: a study on Gaussian measures
May 2022
Intervenant : Hicham Janati
Institution : Télécom Paris
Heure : 15h15
Lieu : 3L15

Since the introduction of entropic regularization to optimal transport, several works investigating its bias as well
as statistical properties have been carried out (debiasing, statistical complexity ..) In this presentation, I will discuss
the various implications of the very definition of entropy: discrete, continuous, semi-discrete and debiased. The first part
of the talk will be dedicated to comparing these formulations (+barycenters) for Gaussian measures. In the second part I will
present generalizations of closed form formulae and some potential conjectures for unbalanced OT (with/and without entropy) as well
as multi-marginal OT.

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