International audienceAlthough optimal transport (OT) problems admit closed form solutions in a very few notable cases, e.g. in 1D or between Gaussians, these closed forms have proved extremely fecund for practitioners to define tools inspired from the OT geometry. On the other hand, the numerical resolution of OT problems using entropic regularization has given rise to many applications, but because there are no known closed-form solutions for entropic regularized OT problems, these approaches are mostly algorithmic, not informed by elegant closed forms. In this paper, we propose to fill the void at the intersection between these two schools of thought in OT by proving that the entropy-regularized optimal transport problem between two Gaus...
We prove several fundamental statistical bounds for entropic OT with the squared Euclidean cost betw...
Inspired by the recent theory of Entropy-Transport problems and by the $\mathbf{D}$-distance of Stur...
We develop a full theory for the new class of Optimal Entropy-Transport problems between nonnegative...
International audienceAlthough optimal transport (OT) problems admit closed form solutions in a very...
Comparing and matching probability distributions is a crucial in numerous machine learning (ML) algo...
The distance that compares the difference between two probability distributions plays a fundamental ...
We analyze optimal transport problems with additional entropic cost evaluated along curves in the Wa...
We analyze optimal transport problems with additional entropic cost evaluated along curves in the Wa...
First version, comments welcome.Using the dual formulation only, we show that regularity of unbalanc...
This work deals with the asymptotic distribution of both potentials and couplings of entropic regula...
Measure of distance between two probability distributions plays a fundamental role in statistics and...
In this thesis we aim at giving a general numerical framework to approximate solutions to optimal tr...
Entropic regularization of optimal transport is appealing both from a numerical and theoretical pers...
We introduce a new second order stochastic algorithm to estimate the entropically regularized optima...
We study the entropic regularization of the optimal transport problem in dimension 1 when the cost f...
We prove several fundamental statistical bounds for entropic OT with the squared Euclidean cost betw...
Inspired by the recent theory of Entropy-Transport problems and by the $\mathbf{D}$-distance of Stur...
We develop a full theory for the new class of Optimal Entropy-Transport problems between nonnegative...
International audienceAlthough optimal transport (OT) problems admit closed form solutions in a very...
Comparing and matching probability distributions is a crucial in numerous machine learning (ML) algo...
The distance that compares the difference between two probability distributions plays a fundamental ...
We analyze optimal transport problems with additional entropic cost evaluated along curves in the Wa...
We analyze optimal transport problems with additional entropic cost evaluated along curves in the Wa...
First version, comments welcome.Using the dual formulation only, we show that regularity of unbalanc...
This work deals with the asymptotic distribution of both potentials and couplings of entropic regula...
Measure of distance between two probability distributions plays a fundamental role in statistics and...
In this thesis we aim at giving a general numerical framework to approximate solutions to optimal tr...
Entropic regularization of optimal transport is appealing both from a numerical and theoretical pers...
We introduce a new second order stochastic algorithm to estimate the entropically regularized optima...
We study the entropic regularization of the optimal transport problem in dimension 1 when the cost f...
We prove several fundamental statistical bounds for entropic OT with the squared Euclidean cost betw...
Inspired by the recent theory of Entropy-Transport problems and by the $\mathbf{D}$-distance of Stur...
We develop a full theory for the new class of Optimal Entropy-Transport problems between nonnegative...