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We study discrete linear divergence-form operators with random coefficients, also known as the random conductance model. We assume that the conductances are bounded, independent and stationary; the law of a conductance may depend on the…

Probability · Mathematics 2017-02-10 Arianna Giunti , Jean-Christophe Mourrat

Cooperative effects of periodic force and noise in globally Cooperative effects of periodic force and noise in globally coupled systems are studied using a nonlinear diffusion equation for the number density. The amplitude of the order…

Chaotic Dynamics · Physics 2009-11-07 Hidetsugu Sakaguchi

In this article a fractional cross-diffusion system is derived as the rigorous many-particle limit of a multi-species system of moderately interacting particles that is driven by L\'{e}vy noise. The form of the mutual interaction is…

Analysis of PDEs · Mathematics 2021-12-08 Esther S. Daus , Mariya Ptashnyk , Claudia Raithel

In the pathwise stochastic calculus framework, the paper deals with the general study of equations driven by an additive Gaussian noise, with a drift function having an infinite limit at point zero. An ergodic theorem and the convergence of…

Probability · Mathematics 2019-01-16 Nicolas Marie

We prove a stochastic homogenization result for a class of \emph{nonlinear} and \emph{nonlocal} variational problems in domains with many small randomly distributed (bilateral) obstacles. Our model case is a Dirichlet problem for the…

Analysis of PDEs · Mathematics 2026-04-14 Francesco Deangelis , Matteo Focardi , Caterina Ida Zeppieri

We study the homogenization of nonlinear, first-order equations with highly oscillatory mixing spatio-temporal dependence. It is shown in a variety of settings that the homogenized equations are stochastic Hamilton-Jacobi equations with…

Analysis of PDEs · Mathematics 2020-09-25 Benjamin Seeger

In this paper, we consider the strong convergence of the time-space fractional diffusion equation driven by fractional Gaussion noise with Hurst index $H\in(\frac{1}{2},1)$. A sharp regularity estimate of the mild solution and the numerical…

Numerical Analysis · Mathematics 2021-01-07 Daxin Nie , Weihua Deng

Scene flow estimation is an essential ingredient for a variety of real-world applications, especially for autonomous agents, such as self-driving cars and robots. While recent scene flow estimation approaches achieve a reasonable accuracy,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-07 Yushan Zhang , Bastian Wandt , Maria Magnusson , Michael Felsberg

We construct a novel estimator for the diffusion coefficient of the limiting homogenized equation, when observing the slow dynamics of a multiscale model, in the case when the slow dynamics are of bounded variation. Previous research…

Statistics Theory · Mathematics 2018-07-04 Theodoros Manikas , Anastasia Papavasiliou

A version of fractional diffusion on bounded domains, subject to 'homogeneous Dirichlet boundary conditions' is derived from a kinetic transport model with homogeneous inflow boundary conditions. For nonconvex domains, the result differs…

Analysis of PDEs · Mathematics 2016-07-05 Pedro Aceves-Sanchez , Christian Schmeiser

In this paper, we investigate the averaging principle for a class of semilinear slow-fast partial differential equations driven by finite-dimensional rough multiplicative noise. Specifically, the slow component is driven by a general random…

Probability · Mathematics 2024-11-26 Miaomiao Li , Yunzhang Li , Bin Pei , Yong Xu

In this paper we establish the strong existence, pathwise uniqueness and a comparison theorem to a stochastic partial differential equation driven by Gaussian colored noise with non-Lipschitz drift, H\"older continuous diffusion…

Probability · Mathematics 2020-06-02 Jie Xiong , Xu Yang

We survey continuous-time generative modeling methods based on transporting a simple reference distribution to a data distribution via stochastic or deterministic dynamics. We present a unified framework in which diffusion models,…

Machine Learning · Computer Science 2026-05-11 Aditya Ranganath , Mukesh Singhal

We establish a simultaneous generalization of It\^o's theory of stochastic and Lyons' theory of rough differential equations. The interest in such a unification comes from a variety of applications, including pathwise stochastic filtering,…

Probability · Mathematics 2025-12-09 Peter K. Friz , Antoine Hocquet , Khoa Lê

The homogenization of one-dimensional acoustic or elastic structures of finite extent is considered. A new homogenization method based on transfer matrices is derived. The new homogenization method may account for variable cross sectional…

Fluid Dynamics · Physics 2022-03-15 Michael B. Muhlestein , Alexei T. Skvortsov

We consider a process given as the solution of a stochastic differential equation with irregular, path dependent and time-inhomogeneous drift coefficient and additive noise. Explicit and optimal bounds for the Lebesgue density of that…

Probability · Mathematics 2015-08-04 David Baños , Paul Krühner

We study the evolution of a system of free fermions in one dimension under the simultaneous effects of coherent tunneling and stochastic Markovian noise. We identify a class of noise terms where a hierarchy of decoupled equations for the…

Statistical Mechanics · Physics 2015-05-27 Viktor Eisler

In the present work, we explore homogenization techniques for a class of switching diffusion processes whose drift and diffusion coefficients, and jump intensities are smooth, spatially periodic functions; we assume full coupling between…

Probability · Mathematics 2025-07-01 Chetan D. Pahlajani

We consider a process given as the solution of a one-dimensional stochastic differential equation with irregular, path dependent and time-inhomogeneous drift coefficient and additive noise. H\"older continuity of the Lebesgue density of…

Probability · Mathematics 2016-04-28 David Baños , Paul Krühner

Diffusions are a successful technique to sample from high-dimensional distributions. The target distribution can be either explicitly given or learnt from a collection of samples. They implement a diffusion process whose endpoint is a…

Machine Learning · Computer Science 2025-09-03 Andrea Montanari