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Adapted or causal transport theory aims to extend classical optimal transport from probability measures to stochastic processes. On a technical level, the novelty is to restrict to couplings which are bicausal, i.e. satisfy a property which…

Probability · Mathematics 2025-10-21 Mathias Beiglböck , Gudmund Pammer , Stefan Schrott

In this paper, we establish a regularity theory for the optimal transport problem when the target is composed of two disjoint convex domains. This is an important model in which singularities arise. Even though the singular set does not…

Analysis of PDEs · Mathematics 2025-07-22 Shibing Chen , Jiakun Liu

We consider the Monge problem of optimal transport between a compactly supported source measure and a target probability measure with unbounded support. We consider the convergence of optimal maps and potential functions when the target…

Numerical Analysis · Mathematics 2026-03-03 Axel G. R. Turnquist

We show continuity of the martingale optimal transport optimisation problem as a functional of its marginals. This is achieved via an estimate on the projection in the nested/causal Wasserstein distance of an arbitrary coupling on to the…

Probability · Mathematics 2022-06-22 Johannes Wiesel

In this paper, we study optimal transportation problems for multifractal random measures. Since these measures are much less regular than optimal transportation theory requires, we introduce a new notion of transportation which is…

Probability · Mathematics 2010-09-02 Rémi Rhodes , Vincent Vargas

Consider the set of probability measures with given marginal distributions on the product of two complete, separable metric spaces, seen as a correspondence when the marginal distributions vary. In problems of optimal transport, continuity…

Risk Management · Quantitative Finance 2020-09-29 Mario Ghossoub , David Saunders

The classical Kantorovich-Rubinstein duality theorem establishes a significant connection between Monge optimal transport and maximization of a linear form on the set of 1-Lipschitz functions. This result has been widely used in various…

Optimization and Control · Mathematics 2025-11-04 Karol Bołbotowski , Guy Bouchitté

In many scientific fields imaging is used to relate a certain physical quantity to other dependent variables. Therefore, images can be considered as a map from a real-world coordinate system to the non-negative measurements being acquired.…

Computer Vision and Pattern Recognition · Computer Science 2018-04-18 Liam Cattell , Gustavo K. Rohde

We introduce a formulation of optimal transport problem for distributions on function spaces, where the stochastic map between functional domains can be partially represented in terms of an (infinite-dimensional) Hilbert-Schmidt operator…

Machine Learning · Statistics 2023-08-29 Jiacheng Zhu , Aritra Guha , Dat Do , Mengdi Xu , XuanLong Nguyen , Ding Zhao

We study multi-marginal optimal transport problems from a probabilistic graphical model perspective. We point out an elegant connection between the two when the underlying cost for optimal transport allows a graph structure. In particular,…

Optimization and Control · Mathematics 2020-06-26 Isabel Haasler , Rahul Singh , Qinsheng Zhang , Johan Karlsson , Yongxin Chen

Under mild regularity assumptions, the transport problem is stable in the following sense: if a sequence of optimal transport plans $\pi_1, \pi_2, \ldots$ converges weakly to a transport plan $\pi$, then $\pi$ is also optimal (between its…

Probability · Mathematics 2020-12-22 Julio Backhoff-Veraguas , Gudmund Pammer

We introduce a new family of intermediate operators between the fractional Laplacian and the Caffarelli-Silvestre nonlocal Monge-Amp\`ere that are given by infimums of integro-differential operators. Using rearrangement techniques, we…

Analysis of PDEs · Mathematics 2024-02-14 Luis A. Caffarelli , María Soria-Carro

This paper presents a variational representation of the Bayes' law using optimal transportation theory. The variational representation is in terms of the optimal transportation between the joint distribution of the (state, observation) and…

Optimization and Control · Mathematics 2022-09-14 Amirhossein Taghvaei , Bamdad Hosseini

Recent advances in large-scale optimal transport have greatly extended its application scenarios in machine learning. However, existing methods either not explicitly learn the transport map or do not support general cost function. In this…

Computer Vision and Pattern Recognition · Computer Science 2020-03-17 Guansong Lu , Zhiming Zhou , Jian Shen , Cheng Chen , Weinan Zhang , Yong Yu

We study the vanishing-regularization limit of entropically regularized optimal transport (EOT) for the Euclidean distance cost $c(x,y)=\|x-y\|$ in dimension $d>1$. We develop a comprehensive variational convergence framework that entails…

Optimization and Control · Mathematics 2026-04-29 Marcel Nutz , Chenyang Zhong

The optimal transportation problem, first suggested by Gaspard Monge in the 18th century and later revived in the 1940s by Leonid Kantorovich, deals with the question of transporting a certain measure to another, using transport maps or…

Optimization and Control · Mathematics 2025-01-24 Shlomi Gover

We consider the numerical solution of the optimal transport problem between densities that are supported on sets of unequal dimension. Recent work by McCann and Pass reformulates this problem into a non-local Monge-Amp\`ere type equation.…

Numerical Analysis · Mathematics 2023-07-14 Matthew A. Cassini , Brittany Froese Hamfeldt

We investigate metric conditions that allow to prove existence and uniqueness of a map solving the Monge problem between two marginals in a metric (measure) space, proving two main results. Firstly, we introduce a nonsmooth version of the…

Metric Geometry · Mathematics 2024-10-31 Shucheng Li , Mattia Magnabosco , Timo Schultz

This paper develops a comprehensive theory of optimal transport for signed (real) measures on Rd. Extending the classical Brenier theorem, we consider Jordan decompositions of measures with possibly fractal singular parts. Under suitable…

Estimating optimal transport (OT) maps (a.k.a. Monge maps) between two measures $P$ and $Q$ is a problem fraught with computational and statistical challenges. A promising approach lies in using the dual potential functions obtained when…

Optimization and Control · Mathematics 2022-06-20 Aram-Alexandre Pooladian , Marco Cuturi , Jonathan Niles-Weed