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We develop a general approach to prove global regularity estimates for quadratic optimal transport using the entropic regularisation of the problem and the Prekopa-Leindler inequality.

Functional Analysis · Mathematics 2025-12-04 Nathael Gozlan , Maxime Sylvestre

In this paper we develop a new approach to nonlinear stochastic partial differential equations with Gaussian noise. Our aim is to provide an abstract framework which is applicable to a large class of SPDEs and includes many important cases…

Functional Analysis · Mathematics 2022-05-02 Antonio Agresti , Mark Veraar

The paper considers the Euler system of PDE on a smooth compact Riemannian manifold of positive curvature without boundary, and the sphere ${\mathbb{S}}^2$ in particular. The paper interprets the Euler equations as a transport problem for…

Analysis of PDEs · Mathematics 2020-11-24 Gordon Blower

The notes are an overview of part of the theory of pathwise weak solutions to two classes of scalar fully nonlinear first- and second-order degenerate parabolic partial differential equations with multiplicative rough time dependence, a…

Analysis of PDEs · Mathematics 2019-09-12 Panagiotis E Souganidis

This work presents a convex-optimization-based framework for analysis and control of nonlinear partial differential equations. The approach uses a particular weak embedding of the nonlinear PDE, resulting in a linear equation in the space…

Optimization and Control · Mathematics 2018-04-23 Milan Korda , Didier Henrion , Jean-Bernard Lasserre

The objective of this paper is to develop a duality between a novel Entropy Martingale Optimal Transport problem (A) and an associated optimization problem (B). In (A) we follow the approach taken in the Entropy Optimal Transport (EOT)…

Mathematical Finance · Quantitative Finance 2021-09-30 Alessandro Doldi , Marco Frittelli

We derive a priori estimates for second order derivatives of solutions to a wide calss of fully nonlinear elliptic equations on Riemannian manifolds. The equations we consider naturally appear in geometric problems and other applications…

Analysis of PDEs · Mathematics 2014-01-30 Bo Guan , Heming Jiao

Optimal transport has gained significant attention in recent years due to its effectiveness in deep learning and computer vision. Its descendant metric, the Wasserstein distance, has been particularly successful in measuring distribution…

Optimization and Control · Mathematics 2025-02-18 Kaiwen Shi

We introduce and study a multi-marginal optimal partial transport problem. Under a natural and sharp condition on the dominating marginals, we establish uniqueness of the optimal plan. Our strategy of proof establishes and exploits a…

Analysis of PDEs · Mathematics 2015-08-10 Jun Kitagawa , Brendan Pass

We propose a numerical algorithm for the computation of multi-marginal optimal transport (MMOT) problems involving general probability measures that are not necessarily discrete. By developing a relaxation scheme in which marginal…

Optimization and Control · Mathematics 2025-12-29 Ariel Neufeld , Qikun Xiang

We investigate the optimal mass transport problem associated to the following "ballistic" cost functional on phase space $M\times M^*$, $$ b_T(v, x):=\inf\{\langle v, \gamma (0)\rangle +\int_0^TL(\gamma (t), {\dot \gamma}(t))\, dt, \gamma…

Analysis of PDEs · Mathematics 2017-06-13 Nassif Ghoussoub

We consider regularised quadratic optimal transport with subquadratic polynomial or entropic regularisation. In both cases, we prove interior Lipschitz-estimates on a transport-like map and interior gradient Lipschitz-estimates on the…

Analysis of PDEs · Mathematics 2026-02-06 Rishabh S. Gvalani , Lukas Koch

We study Jacobi matrices that are uniformly approximated by periodic operators. We show that if the rate of approximation is sufficiently rapid, then the associated quantum dynamics are ballistic in a rather strong sense; namely, the…

Spectral Theory · Mathematics 2017-02-15 Jake Fillman

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

In this paper, we investigate optimal (partial) transport problems for which the target is a non-convex polygonal domain in \(\mathbb{R}^2\). For the complete optimal transport problem, we prove that the singular set is locally a smooth…

Analysis of PDEs · Mathematics 2026-05-19 Shibing Chen , Yuanyuan Li , Jiakun Liu

We study a class of nonlinear nonparametric inverse problems. Specifically, we propose a nonparametric estimator of the dynamics of a monotonically increasing trajectory defined on a finite time interval. Under suitable regularity…

Statistics Theory · Mathematics 2014-08-25 Debashis Paul , Jie Peng , Prabir Burman

Fix a pair of smooth source and target densities $\rho$ and $\rho^*$ of equal mass, supported on bounded domains $\Omega, \Omega^* \subset \mathbb{R}^n$. Also fix a cost function $c_0 \in C^{4,\alpha}(\overline{\Omega} \times…

Analysis of PDEs · Mathematics 2021-08-04 Farhan Abedin , Jun Kitagawa

The study of optimal control problems under uncertainty plays an important role in scientific numerical simulations. This class of optimization problems is strongly utilized in engineering, biology and finance. In this paper, a stochastic…

Optimization and Control · Mathematics 2023-04-06 Caroline Geiersbach , Teresa Scarinci

We introduce and investigate properties of a variant of the semi-discrete optimal transport problem. In this problem, one is given an absolutely continuous source measure and cost function, along with a finite set which will be the support…

Analysis of PDEs · Mathematics 2019-09-13 Mohit Bansil , Jun Kitagawa

We consider a multimarginal optimal transport, which includes as a particular case the Wasserstein barycenter problem. In this problem one has to find an optimal coupling between $m$ probability measures, which amounts to finding a tensor…

Optimization and Control · Mathematics 2020-09-11 Nazarii Tupitsa , Pavel Dvurechensky , Alexander Gasnikov , César A. Uribe