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Distributionally-robust optimization is often studied for a fixed set of distributions rather than time-varying distributions that can drift significantly over time (which is, for instance, the case in finance and sociology due to…

Optimization and Control · Mathematics 2020-10-01 Iman Shames , Farhad Farokhi

This paper presents a finite-dimensional approximation for a class of partial differential equations on the space of probability measures. These equations are satisfied in the sense of viscosity solutions. The main result states the…

Probability · Mathematics 2024-07-24 Mehdi Talbi

Wasserstein gradient flow has emerged as a promising approach to solve optimization problems over the space of probability distributions. A recent trend is to use the well-known JKO scheme in combination with input convex neural networks to…

Machine Learning · Computer Science 2022-07-26 Jiaojiao Fan , Qinsheng Zhang , Amirhossein Taghvaei , Yongxin Chen

We present and study a novel algorithm for the computation of 2-Wasserstein population barycenters of absolutely continuous probability measures on Euclidean space. The proposed method can be seen as a stochastic gradient descent procedure…

Optimization and Control · Mathematics 2023-10-24 Julio Backhoff-Veraguas , Joaquin Fontbona , Gonzalo Rios , Felipe Tobar

This paper presents a systematic study of the relative entropy technique for compressible motions of continuum bodies described as Hamiltonian flows. While the description for the classical mechanics of $N$ particles involves a Hamiltonian…

Analysis of PDEs · Mathematics 2024-02-01 Jan Giesselmann , Kiwoong Kwon , Min-Gi Lee

This article establishes the cutoff phenomenon in the Wasserstein distance for systems of nonlinear ordinary differential equations with a unique coercive stable fixed point subject to general additive Markovian noise in the limit of small…

Probability · Mathematics 2023-05-05 Gerardo Barrera , Michael A. Högele , Juan Carlos Pardo

We prove a Pontryagin Maximum Principle for optimal control problems in the space of probability measures, where the dynamics is given by a transport equation with non-local velocity. We formulate this first-order optimality condition using…

Optimization and Control · Mathematics 2020-02-28 Benoît Bonnet , Francesco Rossi

In this work, we investigate a system of interacting particles governed by a set of stochastic differential equations. Our main goal is to rigorously demonstrate that the empirical measure associated with the particle system converges…

Probability · Mathematics 2025-08-12 Filippo Giovagnini , Dan Crisan

We prove the equivalence between the notion of Wasserstein gradient flow for a one-dimensional nonlocal transport PDE with attractive/repulsive Newtonian potential on one side, and the notion of entropy solution of a Burgers-type scalar…

Analysis of PDEs · Mathematics 2013-10-16 Giovanni A. Bonaschi , José A. Carrillo , Marco Di Francesco , Mark A. Peletier

We derive first-order (in the stepsize) bounds on the bias in Wasserstein distances of the invariant measure of stochastic gradient kinetic Langevin dynamics with minimal assumptions on the stochastic gradient noise. These bounds sharpen…

Computation · Statistics 2026-04-28 Daniel Paulin , Peter A. Whalley

We compute the ground state $u$ of the Gross--Pitaevskii equation (GPE) via Wasserstein gradient descent in diffeomorphism space. We represent the density $\rho=u^2$ as the push-forward of a fixed reference measure through a parameterized…

Numerical Analysis · Mathematics 2026-03-17 Xiangxiong Zhang , Haomin Zhou

It is well-known that the dynamics of vortices in an ideal incompressible two-dimensional fluid contained in a bounded not necessarily simply connected smooth domain is described by the Kirchhoff--Routh point vortex system. In this paper,…

Analysis of PDEs · Mathematics 2020-05-26 Stefano Ceci , Christian Seis

We develop an estimator-based stochastic fixed-point framework for approximately computing the 2-Wasserstein barycenter of continuous, non-parametric probability measures. Notably, we provide the first rigorous convergence analysis for…

Optimization and Control · Mathematics 2026-04-17 Zeyi Chen , Ariel Neufeld , Qikun Xiang

In this paper, we provide bounds in Wasserstein and total variation distances between the distributions of the successive iterates of two functional autoregressive processes with isotropic Gaussian noise of the form $Y_{k+1} =…

Probability · Mathematics 2023-11-30 Alain Durmus , Andreas Eberle , Aurélien Enfroy , Arnaud Guillin , Pierre Monmarché

We propose a variational approach to approximate measures with measures uniformly distributed over a 1 dimentional set. The problem consists in minimizing a Wasserstein distance as a data term with a regularization given by the length of…

Analysis of PDEs · Mathematics 2024-10-17 Antonin Chambolle , Vincent Duval , Joao Miguel Machado

In this paper, we study higher-order-accurate-in-time minimizing movements schemes for Wasserstein gradient flows. We introduce a novel accelerated second-order scheme, leveraging the differential structure of the Wasserstein space in both…

Analysis of PDEs · Mathematics 2025-12-23 Raymond Chu , Matt Jacobs

Purely dissipative evolution equations are often cast as gradient flow structures, $\dot{\mathbf{z}}=K(\mathbf{z})DS(\mathbf{z})$, where the variable $\mathbf{z}$ of interest evolves towards the maximum of a functional $S$ according to a…

Mathematical Physics · Physics 2015-11-18 Celia Reina , Johannes Zimmer

We consider the hydrodynamic behavior of some conservative particle systems with degenerate jump rates without exclusive constraints. More precisely, we study the particle systems without restrictions on the total number of particles per…

Probability · Mathematics 2017-05-01 Makiko Sasada

We consider the (complete) Euler system describing the motion of a compressible perfect fluid. We propose a platform suitable for constructing the statistical solutions. The main ingredients of our approach include: 1. The concept of…

Analysis of PDEs · Mathematics 2026-02-03 Eduard Feireisl

An independence model for discrete random variables is a Segre-Veronese variety in a probability simplex. Any metric on the set of joint states of the random variables induces a Wasserstein metric on the probability simplex. The unit ball…

Optimization and Control · Mathematics 2020-10-16 Türkü Özlüm Çelik , Asgar Jamneshan , Guido Montúfar , Bernd Sturmfels , Lorenzo Venturello