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Dynamical systems that are subject to continuous uncertain fluctuations can be modelled using Stochastic Differential Equations (SDEs). Controlling such system results in solving path constrained SDEs. Broadly, these problems fall under the…

Optimization and Control · Mathematics 2023-06-16 Sumit Suthar , Soumyendu Raha

We establish the existence of smooth densities for solutions to a broad class of path-dependent SDEs under a H\"ormander-type condition. The classical scheme based on the reduced Malliavin matrix turns out to be unavailable in the…

Probability · Mathematics 2021-08-20 Alberto Ohashi , Francesco Russo , Evelina Shamarova

This paper is concerned with semi-linear backward stochastic partial differential equations (BSPDEs for short) of super-parabolic type. An $L^p$-theory is given for the Cauchy problem of BSPDEs, separately for the case of $p\in (1,2]$ and…

Probability · Mathematics 2010-06-08 Kai Du , Jinniao Qiu , Shanjian Tang

Based on a recent result on characterising the path-independence of the Girsanov transformation for non-Lipschnitz stochastic differential equations (SDEs) with jumps on $R^d$, in this paper, we extend our consideration of characterising…

Probability · Mathematics 2018-01-04 Huijie Qiao , Jianglun Wu

We study path-dependent SDEs in Hilbert spaces. By using methods based on contractions in Banach spaces, we prove existence and uniqueness of mild solutions, continuity of mild solutions with respect to perturbations of all the data of the…

Probability · Mathematics 2018-06-22 Mauro Rosestolato

In this paper, we consider the Cauchy problem of semi-linear degenerate backward stochastic partial differential equations (BSPDEs in short) under general settings without technical assumptions on the coefficients. For the solution of…

Probability · Mathematics 2011-09-06 Kai Du , Qi Zhang

Several non-linear operators in stochastic analysis, such as solution maps to stochastic differential equations, depend on a temporal structure which is not leveraged by contemporary neural operators designed to approximate general maps…

Dynamical Systems · Mathematics 2025-04-11 Luca Galimberti , Anastasis Kratsios , Giulia Livieri

We develop a martingale approach for a class of singular stochastic PDEs of Burgers type (including fractional and multi-component Burgers equations) by constructing a domain for their infinitesimal generators. It was known that the domain…

Probability · Mathematics 2018-10-30 Massimiliano Gubinelli , Nicolas Perkowski

In this article, we propose a Milstein finite difference scheme for a stochastic partial differential equation (SPDE) describing a large particle system. We show, by means of Fourier analysis, that the discretisation on an unbounded domain…

Numerical Analysis · Mathematics 2012-04-09 Michael B. Giles , Christoph Reisinger

The rigorous linking of exact stochastic models to mean-field approximations is studied. Starting from the differential equation point of view the stochastic model is identified by its Kolmogorov equations, which is a system of linear ODEs…

Dynamical Systems · Mathematics 2011-09-19 András Bátkai , Istvan Z. Kiss , Eszter Sikolya , Péter L. Simon

We propose a novel numerical approach for nonlocal diffusion equations [8] with integrable kernels, based on the relationship between the backward Kolmogorov equation and backward stochastic differential equations (BSDEs) driven by L\`{e}vy…

Numerical Analysis · Mathematics 2015-07-28 Guannan Zhang , Weidong Zhao , Clayton Webster , Max Gunzburger

We introduce a novel numerical approach for a class of stochastic dynamic programs which arise as discretizations of backward stochastic differential equations or semi-linear partial differential equations. Solving such dynamic programs…

Numerical Analysis · Mathematics 2016-06-24 Christian Bender , Christian Gaertner , Nikolaus Schweizer

We study in this paper the wellposedness of path-dependent multidimensional forward-backward stochastic differential equations (FBSDE). By path-dependent we mean that the coefficients of the forward-backward SDE at time t can depend on the…

Probability · Mathematics 2022-01-13 Kaitong Hu

In this paper, we introduce a new type of backward stochastic differential equations (BSDEs) with infinite anticipation, where the generator depends on the entire future values of the solution in infinite horizon. We show that the new BSDEs…

Probability · Mathematics 2025-11-20 Guanwei Cheng , Shuzhen Yang

In this paper, we present a general framework for solving stochastic functional differential equations in infinite dimensions in the sense of martingale solutions, which can be applied to a large class of SPDE with finite delays, e.g.…

Probability · Mathematics 2014-07-25 Michael Rockner , Rongchan Zhu , Xiangchan Zhu

Both stochastic and PDE modeling approaches have been used and compared in various context in biology. Typically, stochastic models are easier to parameterize, can be used to integrate underlying biological phenomena, but hard to analyze…

Probability · Mathematics 2018-04-17 Xige Yang

In this paper, we consider the backward Cauchy problem of linear degenerate stochastic partial differential equations. We obtain the existence and uniqueness results in Sobolev space $L^p(\Omega; C([0,T];W^{m,p}))$ with both $m\geq 1$ and…

Probability · Mathematics 2011-05-10 Kai Du , Shanjian Tang , Qi Zhang

In this paper, we introduce a class of backward stochastic equations (BSEs) that extend classical BSDEs and include many interesting examples of generalized BSDEs as well as semimartingale backward equations. We show that a BSE can be…

Probability · Mathematics 2017-03-28 Patrick Cheridito , Kihun Nam

We provide necessary and sufficient conditions for stochastic invariance of finite dimensional submanifolds for solutions of stochastic partial differential equations (SPDEs) in continuously embedded Hilbert spaces with non-smooth…

Probability · Mathematics 2025-11-21 Rajeev Bhaskaran , Stefan Tappe

This paper establishes the well-posedness of stochastic partial differential equations with reflection in an infinite-dimensional ball, within the fully local monotone framework. Our result is very general, including many important models…

Probability · Mathematics 2026-05-12 Qi Li , Yue Li , Tusheng Zhang