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We study the Wasserstein gradient flow of semi-discrete energies in the space of probability measures, that is functionals depending on two measures-one being an absolutely continuous density and the other an atomic measure. These energies…

Analysis of PDEs · Mathematics 2026-03-05 Joao Miguel Machado

Wasserstein gradient flows provide a powerful means of understanding and solving many diffusion equations. Specifically, Fokker-Planck equations, which model the diffusion of probability measures, can be understood as gradient descent over…

Machine Learning · Computer Science 2021-10-26 Petr Mokrov , Alexander Korotin , Lingxiao Li , Aude Genevay , Justin Solomon , Evgeny Burnaev

A relaxed notion of displacement convexity is defined and used to establish short time existence and uniqueness of Wasserstein gradient flows for higher order energy functionals. As an application, local and global well-posedness of…

Analysis of PDEs · Mathematics 2012-01-18 Ehsan Kamalinejad

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

This paper is devoted to existence and uniqueness results for classes of nonlinear diffusion equations (or systems) which may be viewed as regular perturbations of Wasserstein gradient flows. First, in the case. where the drift is a…

Analysis of PDEs · Mathematics 2015-05-07 Guillaume Carlier , Maxime Laborde

The theory of Wasserstein gradient flows in the space of probability measures has made an enormous progress over the last twenty years. It constitutes a unified and powerful framework in the study of dissipative partial differential…

Analysis of PDEs · Mathematics 2022-01-17 Daniel Adams , Manh Hong Duong , Goncalo dos Reis

We analyze the gradient flow of a potential energy in the space of probability measures when we substitute the optimal transport geometry with a geometry based on Sinkhorn divergences, a debiased version of entropic optimal transport. This…

Analysis of PDEs · Mathematics 2025-11-19 Mathis Hardion , Hugo Lavenant

We study the quantitative convergence of drift-diffusion PDEs that arise as Wasserstein gradient flows of linearly convex functions over the space of probability measures on ${\mathbb R}^d$. In this setting, the objective is in general not…

Optimization and Control · Mathematics 2025-07-17 Lénaïc Chizat , Maria Colombo , Xavier Fernández-Real

This thesis analyze the Wasserstein gradient flow of a functional defined as a double convolution of a non-smooth repulsive interaction potential. To be more precise, the potential under investigation has a -|x| behavior close to the…

Analysis of PDEs · Mathematics 2013-10-15 Giovanni A. Bonaschi

In this paper we devote our attention to a class of weighted ultrafast diffusion equations arising from the problem of quantisation for probability measures. These equations have a natural gradient flow structure in the space of probability…

Analysis of PDEs · Mathematics 2019-01-30 Mikaela Iacobelli , Francesco Patacchini , Filippo Santambrogio

We study the long time behavior of the Wasserstein gradient flow for an energy functional consisting of two components: particles are attracted to a fixed profile $\omega$ by means of an interaction kernel $\psi_a(z)=|z|^{q_a}$,and they…

Analysis of PDEs · Mathematics 2014-01-13 Marco Di Francesco , Massimo Fornasier , Jan-Christian Hütter , Daniel Matthes

We consider dynamics driven by interaction energies on graphs. We introduce graph analogues of the continuum nonlocal-interaction equation and interpret them as gradient flows with respect to a graph Wasserstein distance. The particular…

Analysis of PDEs · Mathematics 2021-03-17 Antonio Esposito , Francesco S. Patacchini , André Schlichting , Dejan Slepčev

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

Inspired by recent work on minimizers and gradient flows of constrained interaction energies, we prove that these energies arise as the slow diffusion limit of well-known aggregation-diffusion energies. We show that minimizers of…

Analysis of PDEs · Mathematics 2019-05-14 Katy Craig , Ihsan Topaloglu

We consider a class of time-fractional porous medium equations with nonlocal pressure. We show the existence of their weak solutions by proposing a JKO scheme for modified Wasserstein distance and a square fractional Sobolev norm. Moreover,…

Analysis of PDEs · Mathematics 2024-09-16 Nhan-Phu Chung , Thanh-Son Trinh

Wasserstein gradient flow provides a general framework for minimizing an energy functional $J$ over the space of probability measures on a Riemannian manifold $(M,g)$. Its canonical time-discretization, the Jordan-Kinderlehrer-Otto (JKO)…

Machine Learning · Statistics 2026-03-05 Peter Halmos , Boris Hanin

The Poisson-Nernst-Planck system of equations used to model ionic transport is interpreted as a gradient flow for the Wasserstein distance and a free energy in the space of probability measures with finite second moment. A variational…

Analysis of PDEs · Mathematics 2015-09-08 David Kinderlehrer , Léonard Monsaingeon , Xiang Xu

This work is the third part of a program initiated in arXiv:2111.13258, arXiv:2302.06571 aiming at the development of an intrinsic geometric well-posedness theory for Hamilton-Jacobi equations related to controlled gradient flow problems in…

Analysis of PDEs · Mathematics 2024-02-02 Giovanni Conforti , Richard C. Kraaij , Luca Tamanini , Daniela Tonon

In this paper, we start from a very natural system of cross-diffusion equations, which can be seen as a gradient flow for the Wasserstein distance of a certain functional. Unfortunately, the cross-diffusion system is not well-posed, as a…

Analysis of PDEs · Mathematics 2023-07-07 Romain Ducasse , Filippo Santambrogio , Havva Yoldaş

A recurring obstacle in the study of Wasserstein gradient flow is the lack of convexity of the square Wasserstein metric. In this paper, we develop a class of transport metrics that have better convexity properties and use these metrics to…

Analysis of PDEs · Mathematics 2014-06-06 Katy Craig
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