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We consider the stochastic convection-diffusion equation \[ \partial_t u(t\,,{\bf x}) =\nu\Delta u(t\,,{\bf x}) + V(t\,,x_1)\partial_{x_2}u(t\,,{\bf x}), \] for $t>0$ and ${\bf x}=(x_1\,,x_2)\in\mathbb{R}^2$, subject to $\theta_0$ being a…

Probability · Mathematics 2017-11-30 Jingyu Huang , Davar Khoshnevisan

We introduce stochastic normalizing flows, an extension of continuous normalizing flows for maximum likelihood estimation and variational inference (VI) using stochastic differential equations (SDEs). Using the theory of rough paths, the…

Machine Learning · Statistics 2020-02-27 Liam Hodgkinson , Chris van der Heide , Fred Roosta , Michael W. Mahoney

We extend the Ito -to- Stratonovich analysis or quantum stochastic differential equations, introduced by Gardiner and Collett for emission (creation), absorption (annihilation) processes, to include scattering (conservation) processes.…

Mathematical Physics · Physics 2009-11-11 John Gough

We consider stochastic optimization problems involving an expected value of a nonlinear function of a base random vector and a conditional expectation of another function depending on the base random vector, a dependent random vector, and…

Optimization and Control · Mathematics 2024-05-20 Andrzej Ruszczyński , Shangzhe Yang

We discuss a class of stochastic second-order PDEs in one space-dimension with an inner boundary moving according to a possibly non-linear, Stefan-type condition. We show that proper separation of phases is attained, i.e., the solution…

Probability · Mathematics 2018-01-17 Martin Keller-Ressel , Marvin S. Mueller

Researchers from different areas have independently defined extensions of the usual weak convergence of laws of stochastic processes with the goal of adequately accounting for the flow of information. Natural approaches are convergence of…

Probability · Mathematics 2025-01-27 Daniel Bartl , Mathias Beiglböck , Gudmund Pammer , Stefan Schrott , Xin Zhang

The goal of this paper is to prove a convergence rate for Wong-Zakai approximations of semilinear stochastic partial differential equations driven by a finite dimensional Brownian motion. Several examples, including the HJMM equation from…

Probability · Mathematics 2025-11-21 Toshiyuki Nakayama , Stefan Tappe

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

In this paper we consider the It\^o SDE $$d X_t=d W_t+b(t,X_t)\,d t, \quad X_0=x\in {\mathbb R}^d,$$ where $W_t$ is a $d$-dimensional standard Wiener process and the drift coefficient $b:[0,T]\times{\mathbb R}^d\to{\mathbb R}^d$ belongs to…

Probability · Mathematics 2016-05-12 Dejun Luo

We consider stochastic differential equations of the form $dY_t=V(Y_t)\,dX_t+V_0(Y_t)\,dt$ driven by a multi-dimensional Gaussian process. Under the assumption that the vector fields $V_0$ and $V=(V_1,\ldots,V_d)$ satisfy H\"{o}rmander's…

Probability · Mathematics 2015-01-21 Thomas Cass , Martin Hairer , Christian Litterer , Samy Tindel

We study a Wong-Zakai approximation for the random slow manifold of a slow-fast stochastic dynamical system. We first deduce the existence of the random slow manifold about an approximation system driven by an integrated Ornstein-Uhlenbeck…

Dynamical Systems · Mathematics 2018-05-15 Ziying He , Xinyong Zhang , Tao Jiang , Xianming Liu

We introduce a variational theory for processes adapted to the multi-dimensional Brownian motion filtration. The theory provides a differential structure which describes the infinitesimal evolution of Wiener functionals at very small…

Probability · Mathematics 2017-07-13 Alberto Ohashi , Dorival Leão , Alexandre B. Simas

The aim of this paper is to develop a general method for constructing approximation schemes for viscosity solutions of fully nonlinear pathwise stochastic partial differential equations, and for proving their convergence. Our results apply…

Analysis of PDEs · Mathematics 2019-11-01 Benjamin Seeger

We study approximations to a class of vector-valued equations of Burgers type driven by a multiplicative space-time white noise. A solution theory for this class of equations has been developed recently in [Hairer, Weber, Probab. Theory…

Probability · Mathematics 2016-06-02 Martin Hairer , Jan Maas , Hendrik Weber

We consider the ordinary differential equation (ODE) $dx_{t} =b(t,x_{t} ) dt+ dw_{t}$ where $w$ is a continuous driving function and $b$ is a time-dependent vector field which possibly is only a distribution in the space variable. We…

Probability · Mathematics 2016-02-05 R. Catellier , M. Gubinelli

We explore the limit of stochastic differential equations driven by some random processes satisfying singularly perturbed second order stochastic differential equations. The main tool we employ is the universal limit theorem in rough path…

Probability · Mathematics 2026-04-08 Qingming Zhao , Xueru Liu , Wei Wang

We examine the numerical approximation of a quasilinear stochastic differential equation (SDE) with multiplicative fractional Brownian motion. The stochastic integral is interpreted in the Wick-It\^o-Skorohod (WIS) sense that is well…

Numerical Analysis · Mathematics 2026-04-24 Utku Erdogan , Gabriel J. Lord , Roy B. Schieven

In this article we show a robustness theorem for controlled stochastic differential equations driven by approximations of Brownian motion. Often, Brownian motion is used as an idealized model of a diffusion where approximations such as…

Optimization and Control · Mathematics 2023-12-07 Somnath Pradhan , Zachary Selk , Serdar Yüksel

We present a detailed analysis of non-degenerate time-homogeneous It\^o-stochastic differential equations with low local regularity assumptions on the coefficients. In particular the drift coefficient may only satisfy a local integrability…

Probability · Mathematics 2022-09-16 Haesung Lee , Wilhelm Stannat , Gerald Trutnau

We survey recent developments in the field of complexity of pathwise approximation in $p$-th mean of the solution of a stochastic differential equation at the final time based on finitely many evaluations of the driving Brownian motion.…

Probability · Mathematics 2024-03-04 T. Müller-Gronbach , L. Yaroslavtseva