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Related papers: Lagrangian schemes for Wasserstein gradient flows

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Wasserstein gradient flows have become a central tool for optimization problems over probability measures. A natural numerical approach is forward-Euler time discretization. We show, however, that even in the simple case where the energy…

Numerical Analysis · Mathematics 2025-10-16 Yewei Xu , Qin Li

This paper proposes an efficient numerical optimization approach for solving dynamic optimal transport (DOT) problems on general smooth surfaces, computing both the quadratic Wasserstein distance and the associated transportation path.…

Optimization and Control · Mathematics 2025-06-11 Liang Chen , Youyicun Lin , Yuxuan Zhou

The Enskog-like kinetic approach, recently introduced by us to study strongly inhomogeneous flu- ids, is reconsidered in order to improve the description of the transport coefficients. The approach is based on a separation of the…

Statistical Mechanics · Physics 2013-05-01 Umberto Marini Bettolo Marconi , Simone Melchionna

This paper proposes the first free-stream boundary condition in a purely Lagrangian framework for weakly-compressible smoothed particle hydrodynamics (WCSPH). The boundary condition is implemented based on several numerical techniques,…

Fluid Dynamics · Physics 2023-07-04 Shuoguo Zhang , Wenbin Zhang , Chi Zhang , Xiangyu Hu

We consider finite-volume approximations of Fokker-Planck equations on bounded convex domains in $\mathbb{R}^d$ and study the corresponding gradient flow structures. We reprove the convergence of the discrete to continuous Fokker-Planck…

Analysis of PDEs · Mathematics 2020-08-26 Dominik Forkert , Jan Maas , Lorenzo Portinale

We consider degenerate diffusion equations of the form $\partial_tp_t = \Delta f(p_t)$ on a bounded domain and subject to no-flux boundary conditions, for a class of nonlinearities $f$ that includes the porous medium equation. We derive for…

Probability · Mathematics 2022-10-31 Donghan Kim , Lane Chun Yeung

We study laminar thin film flows with large distortions in the free surface using the method of averaging across the flow. Two concrete problems are studied: the circular hydraulic jump and the flow down an inclined plane. For the circular…

Fluid Dynamics · Physics 2007-05-23 Shinya Watanabe , Vachtang Putkaradze , Tomas Bohr

The transport and distribution of organisms like larvae, seeds or litter in the ocean as well as particles in industrial flows is often approximated by a transport of tracer particles. We present a theoretical investigation to check the…

Fluid Dynamics · Physics 2024-07-26 Deoclécio Valente , Ksenia Guseva , Ulrike Feudel

The defining equation $(\ast):\ \dot \omega\_t=-F'(\omega\_t),$ of a gradient flow is kinetic in essence. This article explores some dynamical (rather than kinetic) features of gradient flows (i) by embedding equation $(\ast)$ into the…

Probability · Mathematics 2018-06-11 Ivan Gentil , Christian Léonard , Luigia Ripani

We derive new gradient flows of divergence functions in the probability space embedded with a class of Riemannian metrics. The Riemannian metric tensor is built from the transported Hessian operator of an entropy function. The new gradient…

Information Theory · Computer Science 2019-05-15 Wuchen Li , Lexing Ying

We present the extension of a modeling technique for Lagrangian tracer particles [B. Viggiano et al., J. Fluid Mech.(2020), vol. 900, A27] which accounts for the effects of particle inertia. Thereby, the particle velocity for several Stokes…

Fluid Dynamics · Physics 2021-06-15 J. Friedrich , B. Viggiano , M. Bourgoin , R. B. Cal , L. Chevillard

A numerical scheme for approximating the nonlinear filtering density is introduced and its convergence rate is established, theoretically under a parabolic H\"{o}rmander condition, and empirically in numerical examples. In a prediction…

Numerical Analysis · Mathematics 2026-04-21 Kasper Bågmark , Adam Andersson , Stig Larsson , Filip Rydin

We present a simple approach to study the one-dimensional pressureless Euler system via adhesion dynamics in the Wasserstein space of probability measures with finite quadratic moments. Starting from a discrete system of a finite number of…

Analysis of PDEs · Mathematics 2014-09-16 Luca Natile , Giuseppe Savaré

This paper presents a groundbreaking approach to causal inference by integrating continuous normalizing flows (CNFs) with parametric submodels, enhancing their geometric sensitivity and improving upon traditional Targeted Maximum Likelihood…

Machine Learning · Computer Science 2024-02-02 Kaiwen Hou

We introduce a new version of the KL-divergence for Gaussian distributions which is based on Wasserstein geometry and referred to as WKL-divergence. We show that this version is consistent with the geometry of the sample space ${\Bbb R}^n$.…

Statistics Theory · Mathematics 2026-05-29 Adwait Datar , Nihat Ay

We show that degenerate nonlinear diffusion equations can be asymptotically obtained as a limit from a class of nonlocal partial differential equations. The nonlocal equations are obtained as gradient flows of interaction-like energies…

Analysis of PDEs · Mathematics 2023-10-12 José Antonio Carrillo , Antonio Esposito , Jeremy Sheung-Him Wu

This paper is concerned with the numerical analysis of the explicit Euler scheme for ordinary differential equations with non-Lipschitz vector fields. We prove the convergence of the Euler scheme to regular lagrangian flow (Diperna-Lions…

Classical Analysis and ODEs · Mathematics 2019-09-26 Juan D. Londoño , Christian Olivera

The Landau-Lifshitz Navier-Stokes (LLNS) equations incorporate thermal fluctuations into macroscopic hydrodynamics by using stochastic fluxes. This paper examines explicit Eulerian discretizations of the full LLNS equations. Several CFD…

Numerical Analysis · Mathematics 2009-11-11 John B. Bell , Alejandro L. Garcia , Sarah A. Williams

Recently, Deng et al. (2026) proposed Generative Modeling via Drifting (GMD), a novel framework for generative tasks. This note presents an analysis of GMD through the lens of Wasserstein Gradient Flows (WGF), i.e., the path of steepest…

Machine Learning · Computer Science 2026-05-22 Arthur Gretton , Li Kevin Wenliang , Alexandre Galashov , James Thornton , Valentin De Bortoli , Arnaud Doucet

The squared Wasserstein distance is a natural quantity to compare probability distributions in a non-parametric setting. This quantity is usually estimated with the plug-in estimator, defined via a discrete optimal transport problem which…

Optimization and Control · Mathematics 2020-10-30 Lenaic Chizat , Pierre Roussillon , Flavien Léger , François-Xavier Vialard , Gabriel Peyré