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We introduce a class of high order accurate, semi-implicit Runge-Kutta schemes in the general setting of evolution equations that arise as gradient flow for a cost function, possibly with respect to an inner product that depends on the…

Numerical Analysis · Mathematics 2021-10-04 Alexander Zaitzeff , Selim Esedoglu , Krishna Garikipati

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 work, we investigate a variational formulation for a time-fractional Fokker-Planck equation which arises in the study of complex physical systems involving anomalously slow diffusion. The model involves a fractional-order Caputo…

Numerical Analysis · Mathematics 2020-06-05 Manh Hong Duong , Bangti Jin

In inverse problems, many conditional generative models approximate the posterior measure by minimizing a distance between the joint measure and its learned approximation. While this approach also controls the distance between the posterior…

Machine Learning · Computer Science 2025-08-28 Jannis Chemseddine , Paul Hagemann , Gabriele Steidl , Christian Wald

Otto's (2001) Wasserstein gradient flow of the exclusive KL divergence functional provides a powerful and mathematically principled perspective for analyzing learning and inference algorithms. In contrast, algorithms for the inclusive KL…

Machine Learning · Statistics 2024-11-04 Jia-Jie Zhu

Model Updating is frequently used in Structural Health Monitoring to determine structures' operating conditions and whether maintenance is required. Data collected by sensors are used to update the values of some initially unknown…

Computation · Statistics 2024-01-23 Felipe Igea , Alice Cicirello

We consider a fitness-driven model of dispersal of $N$ interacting populations, which was previously studied merely in the case $N=1$. Based on some optimal transport distance recently introduced, we identify the model as a gradient flow in…

Analysis of PDEs · Mathematics 2016-03-22 Stanislav Kondratyev , Léonard Monsaingeon , Dmitry Vorotnikov

Despite the widespread success of Transformers across various domains, their optimization guarantees in large-scale model settings are not well-understood. This paper rigorously analyzes the convergence properties of gradient flow in…

Machine Learning · Statistics 2024-11-01 Cheng Gao , Yuan Cao , Zihao Li , Yihan He , Mengdi Wang , Han Liu , Jason Matthew Klusowski , Jianqing Fan

We introduce Wasserstein-like dynamical transport distances between vector-valued densities on the real line. The mobility function from the scalar theory is replaced by a mobility matrix, that is subject to positivity and concavity…

Analysis of PDEs · Mathematics 2016-01-18 Jonathan Zinsl , Daniel Matthes

Wasserstein gradient flows of maximum mean discrepancy (MMD) functionals with non-smooth Riesz kernels show a rich structure as singular measures can become absolutely continuous ones and conversely. In this paper we contribute to the…

Machine Learning · Computer Science 2024-03-22 Fabian Altekrüger , Johannes Hertrich , Gabriele Steidl

Gradient flows of the Kullback--Leibler (KL) divergence, such as the Fokker--Planck equation and Stein Variational Gradient Descent, evolve a distribution toward a target density known only up to a normalizing constant. We introduce new…

Machine Learning · Statistics 2026-02-09 Elias Hess-Childs , Dejan Slepčev , Lantian Xu

A detailed analysis is presented to demonstrate the capabilities of the lattice Boltzmann method. Thorough comparisons with other numerical solutions for the two-dimensional, driven cavity flow show that the lattice Boltzmann method gives…

comp-gas · Physics 2009-10-22 Shuling Hou , Qisu Zou , Shiyi Chen , Gary D. Doolen , Allen C. Cogley

We consider a class of time-homogeneous diffusion processes on $\mathbb{R}^{n}$ with common invariant measure but varying volatility matrices. In Euclidean space, we show via stochastic control of the diffusion coefficient that the…

Probability · Mathematics 2023-10-31 Bertram Tschiderer

We study the JKO scheme for the total variation, characterize the optimizers, prove some of their qualitative properties (in particular a form of maximum principle and in some cases, a minimum principle as well). Finally, we establish a…

Analysis of PDEs · Mathematics 2018-07-09 Guillaume Carlier , Clarice Poon

We revisit the variational characterization of conservative diffusion as entropic gradient flow and provide for it a probabilistic interpretation based on stochastic calculus. It was shown by Jordan, Kinderlehrer, and Otto that, for…

Probability · Mathematics 2020-08-24 Ioannis Karatzas , Walter Schachermayer , Bertram Tschiderer

This is a review based on the presentation done at the seminar Laurent Schwartz in December 2021. It is announcing results in the forthcoming [Menegaki-Mouhot-Marahrens'22]. This work presents a new simple quantitative method for proving…

Probability · Mathematics 2022-12-02 Angeliki Menegaki , Clément Mouhot

The propagation of gradient flow structures from microscopic to macroscopic models is a topic of high current interest. In this paper we discuss this propagation in a model for the diffusion of particles interacting via hard-core exclusion…

Analysis of PDEs · Mathematics 2020-08-18 Maria Bruna , Martin Burger , José Antonio Carrillo

We study the large deviation rate functional for the empirical distribution of independent Brownian particles with drift. In one dimension, it has been shown by Adams, Dirr, Peletier and Zimmer that this functional is asymptotically…

Probability · Mathematics 2016-01-11 Matthias Erbar , Jan Maas , Michiel Renger

We consider a one-dimensional aggregation-diffusion equation, which is the gradient flow in the Wasserstein space of a functional with competing attractive-repulsive interactions. We prove that the fully deterministic particle…

Analysis of PDEs · Mathematics 2021-01-01 Sara Daneri , Emanuela Radici , Eris Runa

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
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