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Related papers: Optimal transport of vector measures

200 papers

A recent paper by Cordero-Erausquin and Klartag provides a characterization of the measures $\mu$ on $\R^d$ which can be expressed as the moment measures of suitable convex functions $u$, i.e. are of the form $(\nabla u)\_\\#e^{- u}$ for…

Functional Analysis · Mathematics 2015-07-16 Filippo Santambrogio

We prove a quantitative stability of Kantorovich potentials on metric measure spaces with lower Ricci curvature bound, thereby confirming a recent conjecture of Kitagawa, Letrouit and M\'erigot. Our proof, which employs the heat…

Metric Geometry · Mathematics 2026-03-10 Bang-Xian Han , Zhuo-Nan Zhu

We provide a unifying interpretation of various optimal transport problems as a minimisation of a linear functional over the set of all Choquet representations of a given pair of probability measures ordered with respect to a certain convex…

Functional Analysis · Mathematics 2023-03-06 Krzysztof J. Ciosmak

We investigate the approximation of Monge--Kantorovich problems on general compact metric spaces, showing that optimal values, plans and maps can be effectively approximated via a fully discrete method. First we approximate optimal values…

Numerical Analysis · Mathematics 2024-01-29 Maximiliano Frungillo

The duality theory of the Monge--Kantorovich transport problem is analyzed in a general setting. The spaces $X, Y$ are assumed to be polish and equipped with Borel probability measures $\mu$ and $\nu$. The transport cost function $c:X\times…

Optimization and Control · Mathematics 2010-09-07 Mathias Beiglboeck , Christian Leonard , Walter Schachermayer

We study optimal transport plans from $m$ equally weighted points (with weights $1/m$) to $n$ equally weighted points (with weights $1/n$). The Birkhoff-von Neumann Theorem implies that if $m=n$, then the optimal transport plan can be…

Optimization and Control · Mathematics 2023-12-08 Alexander Bruce Johnson , Stefan Steinerberger

In this essay, we discuss the notion of optimal transport on geodesic measure spaces and the associated (2-)Wasserstein distance. We then examine displacement convexity of the entropy functional on the space of probability measures. In…

Metric Geometry · Mathematics 2012-04-17 Otis Chodosh

We study the optimal transport between two probability measures on the real line, where the transport plans are laws of one-step martingales. A quasi-sure formulation of the dual problem is introduced and shown to yield a complete duality…

Probability · Mathematics 2016-06-14 Mathias Beiglböck , Marcel Nutz , Nizar Touzi

This paper focuses on martingale optimal transport problems when the martingales are assumed to have bounded quadratic variation. First, we give a result that characterizes the existence of a probability measure satisfying some convex…

Probability · Mathematics 2020-03-18 Erhan Bayraktar , Xin Zhang , Zhou Zhou

In this paper, we want to establish some general results in the Lorentzian optimal transport theory that have well-known Riemannian counterparts. As a first result, we will provide non-trivial assumptions on the measures to ensure strong…

Optimization and Control · Mathematics 2026-01-15 Alec Metsch

We study the Optimal Transport problem for laws of random measures in the Kantorovich-Wasserstein space $\mathcal{P}_2(\mathcal{P}_2(\mathrm{H}))$, associated with a Hilbert space $\mathrm{H}$ (with finite or infinite dimension) and for the…

Functional Analysis · Mathematics 2025-09-03 Alessandro Pinzi , Giuseppe Savaré

In this paper we give a new proof of a theorem by Alexandrov on the Gauss curvature prescription of Euclidean convex sets. This proof is based on the duality theory of convex sets and on optimal mass transport. A noteworthy property of this…

Metric Geometry · Mathematics 2015-05-20 Jérôme Bertrand

We develop a full theory for the new class of Optimal Entropy-Transport problems between nonnegative and finite Radon measures in general topological spaces. They arise quite naturally by relaxing the marginal constraints typical of Optimal…

Optimization and Control · Mathematics 2018-10-16 Matthias Liero , Alexander Mielke , Giuseppe Savaré

We develop the optimal transportation approach to modified log-Sobolev inequalities and to isoperimetric inequalities. Various sufficient conditions for such inequalities are given. Some of them are new even in the classical log-Sobolev…

Probability · Mathematics 2007-09-26 Franck Barthe , Alexander V. Kolesnikov

We consider the optimal mass transportation problem in $\RR^d$ with measurably parameterized marginals, for general cost functions and under conditions ensuring the existence of a unique optimal transport map. We prove a joint measurability…

Probability · Mathematics 2008-09-09 Joaquin Fontbona , Helene Guerin , Sylvie Meleard

Using optimal transport we study some dynamical properties of expanding circle maps acting on measures by push-forward. Using the definition of the tangent space to the space of measures introduced by Gigli, their derivative at the unique…

Dynamical Systems · Mathematics 2015-05-22 Benoit Kloeckner

We show that in a locally compact complete $CAT(0)$ space satisfying positive angles property and a disintegration regularity for its canonical Hausdorff measure, there exists a unique optimal transport map that push-forwards a given…

Metric Geometry · Mathematics 2023-03-06 Arian Bërdëllima

In this paper we study two basic facts of optimal transportation on Wiener space W. Our first aim is to answer to the Monge Problem on the Wiener space endowed with the Sobolev type norm (k,gamma) to the power of p (cases p = 1 and p > 1…

Probability · Mathematics 2013-01-25 Vincent Nolot

Caffarelli's contraction theorem bounds the derivative of the optimal transport map between a log-convex measure and a strongly log-concave measure. We show that an analogous phenomenon holds on the level of the trace: The trace of the…

Analysis of PDEs · Mathematics 2025-11-26 Guido De Philippis , Yair Shenfeld

We consider the problem of solving the optimal transport problem between two empirical distributions with missing values. Our main assumption is that the data is missing completely at random (MCAR), but we allow for heterogeneous…

Machine Learning · Statistics 2025-05-26 Linus Bleistein , Aurélien Bellet , Julie Josse