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We discuss diffusion of particles in a spatially inhomogeneous medium. From the microscopic viewpoint we consider independent particles randomly evolving on a lattice. We show that the reversibility condition has a discrete geometric…

Statistical Mechanics · Physics 2018-11-14 Daniele Andreucci , Emilio N. M. Cirillo , Matteo Colangeli , Davide Gabrielli

The well-posedness for SDEs with singularity in both space and distribution variables is derived, where the interacting drift term is bounded and Lipschitz continuous under total variation distance and the diffusion term is allowed to be…

Probability · Mathematics 2025-07-25 Xing Huang

The $L^k$-Wasserstein distance $\mathbb{W}_k (k\ge 1)$ and the probability distance $\mathbb{W}_\psi$ induced by a concave function $\psi$, are estimated between different diffusion processes with singular coefficients. As applications, the…

Probability · Mathematics 2023-11-07 Xing Huang , Panpan Ren , Feng-Yu Wang

We study the initial value problem for a kind of Euler equation with a source term. Our main result is the existence of a globally-in-time weak solution whose total variation is bounded on the the domain of definition, allowing the…

Analysis of PDEs · Mathematics 2019-01-30 Shuyang Xiang , Yangyang Cao

We study existence and long-time behavior of weak solutions to a thin-film equation with a confinement potential and a second-order degenerate diffusion term. It is known that in absence of second order effects, solutions for general…

Analysis of PDEs · Mathematics 2025-05-14 Christian Parsch

The sliced Wasserstein (SW) distance has been widely recognized as a statistically effective and computationally efficient metric between two probability measures. A key component of the SW distance is the slicing distribution. There are…

Machine Learning · Statistics 2024-01-02 Khai Nguyen , Nhat Ho

There has been recently a lot of interest in the analysis of the Stein gradient descent method, a deterministic sampling algorithm. It is based on a particle system moving along the gradient flow of the Kullback-Leibler divergence towards…

Analysis of PDEs · Mathematics 2023-12-29 José A. Carrillo , Jakub Skrzeczkowski

Several issues in machine learning and inverse problems require to generate discrete data, as if sampled from a model probability distribution. A common way to do so relies on the construction of a uniform probability distribution over a…

Optimization and Control · Mathematics 2021-06-16 Quentin Merigot , Filippo Santambrogio , Clément Sarrazin

We perform a mathematical and statistical analysis of the Wasserstein least squares problem, a regression method for vector-valued covariates and distribution-valued responses. Our proposal contrasts with other distributional regression…

Statistics Theory · Mathematics 2026-05-29 Uriel Martínez León , Jonathan Niles-Weed

Let $M$ be a connected compact Riemannian manifold possibly with a boundary, let $V\in C^2(M)$ such that $\mu(\d x):=\e^{V(x)}\d x$ is a probability measure, where $\d x$ is the volume measure, and let $L=\Delta+\nabla V$. The exact…

Probability · Mathematics 2021-07-27 Feng-Yu Wang , Bingyao Wu

This paper considers the problem of regression over distributions, which is becoming increasingly important in machine learning. Existing approaches often ignore the geometry of the probability space or are computationally expensive. To…

Machine Learning · Computer Science 2025-10-31 Maksim Maslov , Alexander Kugaevskikh , Matthew Ivanov

We study the nonlinear wave equation (NLW) on the two-dimensional torus $\mathbb T^2$ with Gaussian random initial data on $H^s(\mathbb T^2) \times H^{s-1}(\mathbb T^2)$, $s < 0$, distributed according to the base Gaussian free field $\mu$…

Analysis of PDEs · Mathematics 2023-02-20 Tadahiro Oh , Mamoru Okamoto , Nikolay Tzvetkov

In this article, we study the problem of sampling from distributions whose densities are not necessarily smooth nor logconcave. We propose a simple Langevin-based algorithm that does not rely on popular but computationally challenging…

Machine Learning · Statistics 2025-12-02 Tim Johnston , Iosif Lytras , Nikolaos Makras , Sotirios Sabanis

In this paper, we initiate the study of the global stability of nonlinear wave equations with initial data that are not required to be localized around a single point. More precisely, we allow small initial data localized around any finite…

Analysis of PDEs · Mathematics 2019-06-07 John Anderson , Federico Pasqualotto

This work is devoted to the Lipschitz contraction and the long time behavior of certain Markov processes. These processes diffuse and jump. They can represent some natural phenomena like size of cell or data transmission over the Internet.…

Probability · Mathematics 2012-10-12 Bertrand Cloez

In finite-dimensions, minimal surfaces that fill in the space delineated by closed curves and have minimal area arose naturally in classical physics in several contexts. No such concept seems readily available in infinite dimensions. The…

Optimization and Control · Mathematics 2023-06-27 Wuchen Li , Tryphon T. Georgiou

We analyze the Drinfeld-Sokolob-Wilson system, which features a dispersive, KdV type evolution with a dispersionless conservation law. We establish well-posedness with low regularity initial data $L^2({\mathbb T})\times L^2({\mathbb T})$…

Analysis of PDEs · Mathematics 2025-02-21 Ognyan Christov , Sevdzhan Hakkaev , Seungly Oh , Atanas G. Stefanov

By using a classical truncated argument and introducing the local Wasserstein distance, the global existence and uniqueness are proved for the distribution dependent SDEs with local Lipschitz coefficients. Due to the measure dependence, the…

Probability · Mathematics 2021-03-25 Shan-Shan Hu

Energy diffusion due to spontaneous localization (SL) for a relativistically-fast moving particle is examined. SL is an alternative to standard quantum theory in which quantum state reduction is treated as a random physical process which is…

Quantum Physics · Physics 2013-09-04 Daniel Bedingham

We construct a gauge theoretic change of variables for the wave map from $R \times R^n$ into a compact group or Riemannian symmetric space, prove a new multiplication theorem for mixed Lebesgue-Besov spaces, and show the global…

Analysis of PDEs · Mathematics 2007-05-23 Andrea Nahmod , Atanas Stefanov , Karen Uhlenbeck