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Related papers: On Time Uniform Wong-Zakai Approximation Theorems

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We consider a Poisson equation in $\mathbb R^d$ for the elliptic operator corresponding to an ergodic diffusion process. Optimal regularity and smoothness with respect to the parameter are obtained under mild conditions on the coefficients.…

Probability · Mathematics 2020-09-11 Michael Röckner , Longjie Xie

Despite the remarkable empirical success of score-based diffusion models, their statistical guarantees remain underdeveloped. Existing analyses often provide pessimistic convergence rates that do not reflect the intrinsic low-dimensional…

Machine Learning · Statistics 2026-04-24 Saptarshi Chakraborty , Quentin Berthet , Peter L. Bartlett

In this work, we are interested in building the fully discrete scheme for stochastic fractional diffusion equation driven by fractional Brownian sheet which is temporally and spatially fractional with Hurst parameters $H_{1}, H_{2}…

Numerical Analysis · Mathematics 2022-01-27 Daxin Nie , Jing Sun , Weihua Deng

This work is aimed at the derivation of reliable and efficient a posteriori error estimates for convection-dominated diffusion problems motivated by a linear Fokker-Planck problem appearing in computational neuroscience. We obtain…

Numerical Analysis · Computer Science 2018-05-16 Svetlana Matculevich , Monika Wolfmayr

We propose a novel small time approximation for the solution to the Zakai equation from nonlinear filtering theory. We prove that the unnormalized filtering density is well described over short time intervals by the solution of a…

Probability · Mathematics 2021-05-27 Alberto Lanconelli , Ramiro Scorolli

The Wong-Zakai theorem asserts that ODEs driven by "reasonable" (e.g. piecewise linear) approximations of Brownian motion converge to the corresponding Stratonovich stochastic differential equation. With the aid of rough path analysis, we…

Probability · Mathematics 2009-03-26 Peter Friz , Harald Oberhauser

In this paper we obtain a Wong-Zakai approximation to solutions of backward doubly stochastic differential equations.

Probability · Mathematics 2014-08-05 Ying Hu , Anis Matoussi , Tusheng Zhang

The diffusion equation and its time-fractional counterpart can be obtained via the diffusion limit of continuous-time random walks with exponential and heavy-tailed waiting time distributions. The space dependent variable-order…

Statistical Mechanics · Physics 2025-10-24 Christopher N. Angstmann , Daniel S. Han , Bruce I. Henry , Boris Z. Huang , Zhuang Xu

In this work, we demonstrate the Wong-Zakai approximation results for two and three dimensional stochastic convective Brinkman-Forchheimer (SCBF) equations forced by Hilbert space valued Wiener noise on bounded domains. Even though the…

Probability · Mathematics 2022-02-24 Kush Kinra , Manil T. Mohan

We provide an explicit rigorous derivation of a diffusion limit - a stochastic differential equation with additive noise - from a deterministic skew-product flow. This flow is assumed to exhibit time-scale separation and has the form of a…

Dynamical Systems · Mathematics 2015-05-27 I. Melbourne , A. M. Stuart

The problem of the time required for a diffusing molecule, within a large bounded domain, to first locate a small target is prevalent in biological modeling. Here we study this problem for a small spherical target. We develop uniform in…

Biological Physics · Physics 2013-08-06 Samuel A. Isaacson , Jay Newby

In this article we study the numerical approximation of a variable coefficient fractional diffusion equation. Using a change of variable, the variable coefficient fractional diffusion equation is transformed into a constant coefficient…

Numerical Analysis · Mathematics 2019-02-28 Xiangcheng Zheng , V. J. Ervin , Hong Wang

In this article we study effects that small perturbations in the noise have to the solution of differential equations driven by H\"older continuous functions of order $H>\frac12$. As an application, we consider stochastic differential…

Probability · Mathematics 2020-05-11 Lauri Viitasaari , Caibin Zeng

Existing deterministic variational inference approaches for diffusion processes use simple proposals and target the marginal density of the posterior. We construct the variational process as a controlled version of the prior process and…

Machine Learning · Computer Science 2021-03-02 Christian Wildner , Heinz Koeppl

The paper examines stochastic diffusion within an expanding space-time framework. It starts with providing a rationale for the considered model and its motivation from cosmology where the expansion of space-time is used in modelling various…

Probability · Mathematics 2023-12-22 Philip Broadbridge , Illia Donhauzer , Andriy Olenko

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

This paper investigates the convergence of Wong--Zakai approximations to regime-switching stochastic differential equations, generated by a collection of finite-variation approximations to Brownian motion. We extend the results of Nguyen…

Probability · Mathematics 2023-04-21 Jasper Barr , Giang T. Nguyen , Oscar Peralta

We construct Wong--Zakai approximations of time--inhomogeneous stochastic differential equations with regime switching (RSSDEs), and provide a convergence rate. %Given a family of finite-variation processes…

Probability · Mathematics 2021-10-12 Giang T. Nguyen , Oscar Peralta

This article studies the quasi-stationary behaviour of absorbed one-dimensional diffusions. We obtain necessary and sufficient conditions for the exponential convergence to a unique quasi-stationary distribution in total variation,…

Probability · Mathematics 2017-03-03 Nicolas Champagnat , Denis Villemonais

We address the long time behaviour of weakly interacting diffusive particle systems on the d-dimensional torus. Our main result is to show that, under certain regularity conditions, the weak error between the empirical distribution of the…

Analysis of PDEs · Mathematics 2025-05-13 François Delarue , Alvin Tse