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Recent advances in deep learning makes solving parabolic partial differential equations (PDEs) in high dimensional spaces possible via forward-backward stochastic differential equation (FBSDE) formulations. The implementation of most…

Numerical Analysis · Mathematics 2025-06-19 Wenjun Xu , Wenzhong Zhang

We obtain existence results for the solution u of nonlocal semilinear parabolic PDEs on $\mathbb{R}^d$ with polynomial nonlinearities in $(u, \nabla u)$, using a tree-based probabilistic representation. This probabilistic representation…

Probability · Mathematics 2021-06-24 Guillaume Penent , Nicolas Privault

In this paper, we study the homogenization of the third boundary value problem for semilinear parabolic PDEs with rapidly oscillating periodic coefficients in the weak sense. Our method is entirely probabilistic, and builds upon the work of…

Probability · Mathematics 2024-06-25 Junxia Duan , Jun Peng

High-dimensional partial-differential equations (PDEs) arise in a number of fields of science and engineering, where they are used to describe the evolution of joint probability functions. Their examples include the Boltzmann and…

Numerical Analysis · Mathematics 2018-10-17 A. M. P. Boelens , D. Venturi , D. M. Tartakovsky

In this work we present a data-driven method for the discovery of parametric partial differential equations (PDEs), thus allowing one to disambiguate between the underlying evolution equations and their parametric dependencies. Group…

Numerical Analysis · Mathematics 2018-06-05 Samuel Rudy , Alessandro Alla , Steven L. Brunton , J. Nathan Kutz

In this work the existence of solutions of one-dimensional backward dou- bly stochastic differential equations (BDSDEs in short) where the coefficient is left-Lipschitz in y (may be discontinuous) and Lipschitz in z is studied. Also, the…

Probability · Mathematics 2010-05-17 Qingfeng Zhu , Yufeng Shi

We define fully coupled forward-backward stochastic differential equations on spaces related to continuous time, finite state Markov Chains. Existence and uniqueness results of the fully coupled forward-backward stochastic differential…

Probability · Mathematics 2015-04-29 Shaolin Ji , Haodong Liu , Xinling Xiao

Motivated by Girsanov's nonuniqueness examples for SDEs, we prove nonuniqueness for the parabolic stochastic partial differential equation (SPDE) \[\frac{\partial u}{\partial t}=\frac{\Delta}{2}u(t,x)…

Probability · Mathematics 2014-09-04 Carl Mueller , Leonid Mytnik , Edwin Perkins

In this paper, we prove that, if the coefficient f = f(t; y; z) of backward doubly stochastic differential equations (BDSDEs for short) is assumed to be continuous and linear growth in (y; z); then the uniqueness of solution and continuous…

Probability · Mathematics 2010-05-17 Qingfeng Zhu , Yufeng Shi

In multi-phase fluid flow, fluid-structure interaction, and other applications, partial differential equations (PDEs) often arise with discontinuous coefficients and singular sources (e.g., Dirac delta functions). These complexities arise…

Numerical Analysis · Mathematics 2019-07-24 Chung-Nan Tzou , Samuel Stechmann

A coupled forward-backward stochastic differential system (FBSDS) is formulated in spaces of fields for the incompressible Navier-Stokes equation in the whole space. It is shown to have a unique local solution, and further if either the…

Mathematical Physics · Physics 2014-03-04 Freddy Delbaen , Jinniao Qiu , Shanjian Tang

In this paper we study the existence of stationary solutions for stochastic partial differential equations. We establish a new connection between $L_{\rho}^2({\mathbb{R}^{d}};{\mathbb{R}^{1}}) \otimes…

Probability · Mathematics 2008-11-13 Qi Zhang , Huaizhong Zhao

In this article we study the differentiability of solutions of parabolic semilinear stochastic evolution equations (SEEs) with respect to their initial values. We prove that if the nonlinear drift coefficients and the nonlinear diffusion…

Probability · Mathematics 2021-11-02 Adam Andersson , Arnulf Jentzen , Ryan Kurniawan , Timo Welti

We consider one-dimensional hyperbolic PDEs, linear and nonlinear, with random initial data. Our focus is the {\em pointwise statistics,} i.e., the probability measure of the solution at any fixed point in space and time. For linear…

Analysis of PDEs · Mathematics 2025-12-17 Alina Chertock , Pierre Degond , Amir Sagiv , Li Wang

Motivated by earlier work on the use of fully-coupled Forward-Backward Stochastic Differential Equations (henceforth FBSDEs) in the analysis of mathematical models for the CO2 emissions markets, the present study is concerned with the…

Probability · Mathematics 2012-10-23 Rene Carmona , Francois Delarue

This paper presents existence and uniqueness results for reflected system of quasilinear stochastic partial differential equations in a convex domain D from Rk. The method is based on the probabilistic interpretation of the solution by…

Probability · Mathematics 2018-01-03 Wissal Sabbagh , Tusheng Zhang

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

We prove an existence and uniqueness result for the obstacle problem of quasilinear parabolic stochastic PDEs. The method is based on the probabilistic interpretation of the solution by using the backward doubly stochastic differential…

Probability · Mathematics 2010-10-13 Anis Matoussi , Lucretiu Stoica

We propose a nonlinear forward Feynman-Kac type equation, which represents the solution of a non-conservative semilinear parabolic Partial Differential Equations (PDE). We show in particular existence and uniqueness. The solution of that…

Probability · Mathematics 2018-10-05 Anthony Lecavil , Anthony Le Cavil , Nadia Oudjane , Francesco Russo

We study function-valued solutions of a class of stochastic partial differential equations, involving operators with polynomially bounded coefficients. We consider semilinear equations under suitable parabolicity hypotheses. We provide…

Probability · Mathematics 2022-06-16 Alessia Ascanelli , Sandro Coriasco , André Suß
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