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We propose a fully discrete variational scheme for nonlinear evolution equations with gradient flow structure on the space of finite Radon measures on an interval with respect to a generalized version of the Wasserstein distance with…

Numerical Analysis · Mathematics 2016-09-29 Jonathan Zinsl , Daniel Matthes

In this article we set up a splitting variant of the JKO scheme in order to handle gradient flows with respect to the Kantorovich-Fisher-Rao metric, recently introduced and defined on the space of positive Radon measure with varying masses.…

Analysis of PDEs · Mathematics 2018-05-08 Thomas Gallouët , Léonard Monsaingeon

This article details a novel numerical scheme to approximate gradient flows for optimal transport (i.e. Wasserstein) metrics. These flows have proved useful to tackle theoretically and numerically non-linear diffusion equations that model…

Optimization and Control · Mathematics 2015-03-10 Gabriel Peyré

The so-called JKO scheme, named after Jordan, Kinderlehrer and Otto, provides a variational way to construct discrete time approximations of certain partial differential equations (PDEs) appearing as gradient flows in the space of…

Analysis of PDEs · Mathematics 2026-04-10 Aymeric Baradat , Sofiane Cherf

The seminal paper of Jordan, Kinderlehrer, and Otto introduced what is now widely known as the JKO scheme, an iterative algorithmic framework for computing distributions. This scheme can be interpreted as a Wasserstein gradient flow and has…

Machine Learning · Statistics 2025-01-15 Shang Wu , Yazhen Wang

Algorithms based on discretizing Langevin diffusion are popular tools for sampling from high-dimensional distributions. We develop novel connections between such Monte Carlo algorithms, the theory of Wasserstein gradient flow, and the…

Computation · Statistics 2019-05-13 Espen Bernton

A nonlinear diffusion equation, interpreted as a Wasserstein gradient flow, is numerically solved in one space dimension using a higher-order minimizing movement scheme based on the BDF (backward differentiation formula) discretization. In…

Numerical Analysis · Mathematics 2015-09-02 Bertram Düring , Philipp Fuchs , Ansgar Jüngel

We study families of porous medium equation with nonlocal pressure. We construct their weak solutions via JKO schemes for modified Wasserstein distances. We also establish the regularization effect and decay estimates for the $L^p$ norms.

Analysis of PDEs · Mathematics 2022-05-24 Nhan-Phu Chung , Quoc-Hung Nguyen

We present a method to efficiently compute Wasserstein gradient flows. Our approach is based on a generalization of the back-and-forth method (BFM) introduced by Jacobs and L\'eger to solve optimal transport problems. We evolve the gradient…

Numerical Analysis · Mathematics 2020-11-17 Matt Jacobs , Wonjun Lee , Flavien Léger

In this article, we report the results we obtained when investigating the numerical solution of some nonlinear eigenvalue problems for the Monge-Amp\`{e}re operator $v\rightarrow \det \mathbf{D}^2 v$. The methodology we employ relies on the…

Numerical Analysis · Mathematics 2020-09-11 Roland Glowinski , Shingyu Leung , Hao Liu , Jianliang Qian

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

We introduce a novel spatio-temporal discretization for nonlinear Fokker-Planck equations on the multi-dimensional unit cube. This discretization is based on two structural properties of these equations: the first is the representation as a…

Numerical Analysis · Mathematics 2016-01-11 Oliver Junge , Daniel Matthes , Horst Osberger

The Wasserstein gradient flow structure of the PDE system governing multiphase flows in porous media was recently highlighted in [C. Canc\`es, T. O. Gallou\"et, and L. Monsaingeon, {\it Anal. PDE} 10(8):1845--1876, 2017]. The model can thus…

Numerical Analysis · Mathematics 2018-07-23 Clément Cancès , Thomas O. Gallouët , Maxime Laborde , Léonard Monsaingeon

The purpose of this work is mostly expository and aims to elucidate the Jordan-Kinderlehrer-Otto (JKO) scheme for uncertainty propagation, and a variant, the Laugesen-Mehta-Meyn-Raginsky (LMMR) scheme for filtering. We point out that these…

Optimization and Control · Mathematics 2017-10-03 Abhishek Halder , Tryphon T. Georgiou

We give the solution of the Monge-Kantorovitch problem on the Wiener space for the singular Wasserstein metric which is defined with respect to the distance of the underlying Cameron-Martin space. We show, under the hypothesis that this…

Probability · Mathematics 2007-05-23 D. Feyel , A. S. Ustunel

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

We present a novel approximate inference method for diffusion processes, based on the Wasserstein gradient flow formulation of the diffusion. In this formulation, the time-dependent density of the diffusion is derived as the limit of…

Machine Learning · Statistics 2018-06-13 Charlie Frogner , Tomaso Poggio

We propose a two-scale finite element method for the Monge-Amp\`ere equation with Dirichlet boundary condition in dimension $d\ge2$ and prove that it converges to the viscosity solution uniformly. The method is inspired by a finite…

Numerical Analysis · Mathematics 2018-04-16 Ricardo H. Nochetto , Dimitrios Ntogkas , Wujun Zhang

This paper contains two contributions in the study of optimal transport on metric graphs. Firstly, we prove a Benamou-Brenier formula for the Wasserstein distance, which establishes the equivalence of static and dynamical optimal transport.…

Analysis of PDEs · Mathematics 2022-05-02 Matthias Erbar , Dominik Forkert , Jan Maas , Delio Mugnolo

The Jordan-Kinderlehrer-Otto (JKO) scheme provides a stable variational framework for computing Wasserstein gradient flows, but its practical use is often limited by the high computational cost of repeatedly solving the JKO subproblems. We…

Machine Learning · Computer Science 2026-01-12 Xue Feng , Li Wang , Deanna Needell , Rongjie Lai