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Related papers: Optimal transportation between unequal dimensions

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We study Neural Optimal Transport in infinite-dimensional Hilbert spaces. In non-regular settings, Semi-dual Neural OT often generates spurious solutions that fail to accurately capture target distributions. We analytically characterize…

Machine Learning · Computer Science 2026-02-17 Jae-Hwan Choi , Jiwoo Yoon , Dohyun Kwon , Jaewoong Choi

Optimal transport problems pose many challenges when considering their numerical treatment. We investigate the solution of a PDE-constrained optimisation problem subject to a particular transport equation arising from the modelling of image…

Numerical Analysis · Mathematics 2018-01-15 Roland Herzog , John W. Pearson , Martin Stoll

The Gromov--Wasserstein problem is a non-convex optimization problem over the polytope of transportation plans between two probability measures supported on two spaces, each equipped with a cost function evaluating similarities between…

Optimization and Control · Mathematics 2024-07-30 Théo Dumont , Théo Lacombe , François-Xavier Vialard

In this paper, we establish the global $W^{2,p}$ estimate for the Monge-Amp\`ere obstacle problem: $(Du)_{\sharp}f\chi{_{\{u>\frac{1}{2}|x|^2\}}}=g$, where $f$ and $g$ are positive continuous functions supported in disjoint bounded $C^2$…

Analysis of PDEs · Mathematics 2023-07-04 Shibing Chen , Jiakun Liu , Xianduo Wang

This is an expository paper describing how duality theory for Hessian manifolds provides a natural setting for optimal transport. We explain how this can be used to solve Monge-Amp\`ere equations and survey recent results along these lines…

Differential Geometry · Mathematics 2023-06-22 Jakob Hultgren

This paper is devoted to variational problems on the set of probability measures which involve optimal transport between unequal dimensional spaces. In particular, we study the minimization of a functional consisting of the sum of a term…

Analysis of PDEs · Mathematics 2019-11-18 Luca Nenna , Brendan Pass

The dynamical formulation of optimal transport, also known as Benamou-Brenier formulation or Computational Fluid Dynamics formulation, amounts to write the optimal transport problem as the optimization of a convex functional under a PDE…

Numerical Analysis · Mathematics 2020-05-25 Hugo Lavenant

Optimal transport has emerged as a fundamental methodology with applications spanning multiple research areas in recent years. However, the convergence rate of the empirical estimator to its population counterpart suffers from the curse of…

Statistics Theory · Mathematics 2025-10-06 Jiaping Yang , Yunxin Zhang

We prove existence and uniqueness results for solutions to a class of optimal transportation problems with infinitely many marginals, supported on the real line. We also provide a characterization of the solution with an explicit formula.…

Optimization and Control · Mathematics 2012-06-26 Brendan Pass

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

We analyze optimal transport problems with additional entropic cost evaluated along curves in the Wasserstein space which join two probability measures $m_0,m_1$. The effect of the additional entropy functional results into an elliptic…

Analysis of PDEs · Mathematics 2022-11-18 Alessio Porretta

We consider a PDE approach to numerically solving the optimal transportation problem on the sphere. We focus on both the traditional squared geodesic cost and a logarithmic cost, which arises in the reflector antenna design problem. At each…

Numerical Analysis · Mathematics 2021-07-09 Brittany Froese Hamfeldt , Axel G. R. Turnquist

We propose an extension of the computational fluid mechanics approach to the Monge-Kantorovich mass transfer problem, which was developed by Benamou-Brenier. Our extension allows optimal transfer of unnormalized and unequal masses. We…

Optimization and Control · Mathematics 2019-10-23 Wilfrid Gangbo , Wuchen Li , Stanley Osher , Michael Puthawala

The purpose of this paper is to show that in a finite dimensional metric space with Alexandrov's curvature bounded below, Monge's transport problem for the quadratic cost admits a unique solution.

Differential Geometry · Mathematics 2007-05-23 Jerome Bertrand

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

In this note, we propose polynomial-time algorithms solving the Monge and Kantorovich formulations of the $\infty$-optimal transport problem in the discrete and finite setting. It is the first time, to the best of our knowledge, that…

Optimization and Control · Mathematics 2023-04-27 Meyer Scetbon

The convexity of solutions to boundary value problems for fully nonlinear elliptic partial differential equations (such as real or complex $k$-Hessian equations) is a challenging topic. In this paper, we establish the power convexity of…

Analysis of PDEs · Mathematics 2025-08-01 Wei Zhang , Qi Zhou

Optimal Transport (OT) problems arise in a wide range of applications, from physics to economics. Getting numerical approximate solution of these problems is a challenging issue of practical importance. In this work, we investigate the…

Probability · Mathematics 2019-05-15 Aurélien Alfonsi , Rafaël Coyaud , Virginie Ehrlacher , Damiano Lombardi

The optimal (Monge-Kantorovich) transportation problem is discussed from several points of view. The Lagrangian formulation extends the action of the {\em Lagrangian} $L(v,x,t)$ from the set of orbits in $\R^n$ to a set of measure-valued…

Mathematical Physics · Physics 2007-05-23 Gershon Wolansky

Many problems in machine learning involve calculating correspondences between sets of objects, such as point clouds or images. Discrete optimal transport provides a natural and successful approach to such tasks whenever the two sets of…

Machine Learning · Statistics 2019-02-28 David Alvarez-Melis , Stefanie Jegelka , Tommi S. Jaakkola