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Backward stochastic differential equation (BSDE) provides probabilistic solutions for a class of parabolic partial differential equations (PDEs). DeepBSDE and FBSNN are two deep learning approaches for solving high-dimensional PDEs through…

Numerical Analysis · Mathematics 2026-04-29 Zhao Zhang , Zhuopeng Hou

In this paper, we study an optimal control problem of linear backward stochastic differential equation (BSDE) with quadratic cost functional under partial information. This problem is solved completely and explicitly by using a stochastic…

Optimization and Control · Mathematics 2020-12-16 Guangchen Wang , Wencan Wang , Zhiguo Yan

The present paper is devoted to investigating the existence and uniqueness of solutions to a class of non-Lipschitz scalar valued backward stochastic differential equations driven by $G$-Brownian motion ($G$-BSDEs). In fact, when the…

Probability · Mathematics 2020-12-03 Falei Wang , Guoqiang Zheng

In this paper we are concerned with one-dimensional backward stochastic differential equations (BSDE in short) of the following type: \[Y_t=\xi -\int_{t\wedge \tau}^{\tau}Y_r|Y_r|^q dr-\int_{t\wedge \tau}^{\tau}Z_r dB_r,\qquad t\geq 0,\]…

Probability · Mathematics 2009-09-29 A. Popier

In this note, we present a new numerical method for solving backward stochastic differential equations. Our method can be viewed as an analogue of the classical finite element method solving deterministic partial differential equations.

Probability · Mathematics 2011-06-07 Penghui Wang , Xu Zhang

The numerical solution of differential equations can be formulated as an inference problem to which formal statistical approaches can be applied. However, nonlinear partial differential equations (PDEs) pose substantial challenges from an…

Numerical Analysis · Mathematics 2021-08-26 Junyang Wang , Jon Cockayne , Oksana Chkrebtii , T. J. Sullivan , Chris. J. Oates

For the stochastic differential equation (SDE) which has piecewise continuous arguments (PCAs), is driven by multiplicative noises and its drift coefficients are dissipative, we show that the solution at integer time is a Markov chain and…

Numerical Analysis · Mathematics 2024-09-23 Chuchu Chen , Jialin Hong , Yulan Lu

In this paper, we deal with a class of one-dimensional reflected backward stochastic differential equations with stochastic Lipschitz coefficient. We derive the existence and uniqueness of the solutions for those equations via Snell…

Probability · Mathematics 2015-01-06 Wen Lu

In this paper we introduce a multilevel Picard approximation algorithm for general semilinear parabolic PDEs with gradient-dependent nonlinearities whose coefficient functions do not need to be constant. We also provide a full convergence…

Numerical Analysis · Mathematics 2025-02-19 Ariel Neufeld , Sizhou Wu

This paper is an attempt to extend the notion of viscosity solution to nonlinear stochastic partial differential integral equations with nonlinear Neumann boundary condition. Using the recently developed theory on generalized backward…

Probability · Mathematics 2010-11-16 Auguste Aman , Yong Ren

There is recent interest in finding a potential formulation for Stochastic Partial Differential Equations (SPDEs). The rationale behind this idea lies in obtaining all the dynamical information of the system under study from one single…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 A. G. Munoz , J. Ojeda , D. Sierra , T. Soldovieri

We propose a new method for the numerical solution of the forward-backward stochastic differential equations (FBSDE) appearing in the Feynman-Kac representation of the value function in stochastic optimal control problems. Using Girsanov's…

Optimization and Control · Mathematics 2022-10-20 Kelsey P. Hawkins , Ali Pakniyat , Evangelos Theodorou , Panagiotis Tsiotras

We propose a new algorithm to approach weakly the solution of a McKean-Vlasov SDE. Based on the cubature method of Lyons and Victoir 2004, the algorithm is deterministic differing from the the usual methods based on interacting particles.…

Probability · Mathematics 2019-04-22 Paul-Eric Chaudru de Raynal , Camilo Garcia Trillos

In this paper, we study the backward stochastic differential equation (BSDE) with two nonlinear mean reflections, which means that the constraints are imposed on the distribution of the solution but not on its paths. Based on the backward…

Probability · Mathematics 2023-07-13 Hanwu Li

In this paper, we define a notion of second-order backward stochastic differential equations with jumps (2BSDEJs for short), which generalizes the continuous case considered by Soner, Touzi and Zhang [Probab. Theory Related Fields 153…

Probability · Mathematics 2015-09-10 Nabil Kazi-Tani , Dylan Possamaï , Chao Zhou

In this paper, we present a backward deep BSDE method applied to Forward Backward Stochastic Differential Equations (FBSDE) with given terminal condition at maturity that time-steps the BSDE backwards. We present an application of this…

Computational Finance · Quantitative Finance 2020-06-16 Yajie Yu , Bernhard Hientzsch , Narayan Ganesan

In this paper, we are concerned with the numerical solution for the backward fractional Feynman-Kac equation with non-smooth initial data. Here we first provide the regularity estimate of the solution. And then we use the backward Euler and…

Numerical Analysis · Mathematics 2020-06-23 Jing Sun , Daxin Nie , Weihua Deng

This paper is concerned with the existence and uniqueness of weak solutions to the Cauchy-Dirichlet problem of backward stochastic partial differential equations (BSPDEs) with nonhomogeneous terms of quadratic growth in both the gradient of…

Probability · Mathematics 2012-07-24 Kai Du , Shaokuan Chen

This paper first studies super linear G-expectation. Uniqueness and existence theorem for backward stochastic differential equations (BSDEs) under super linear expectation is established to provide probabilistic interpretation for the…

Probability · Mathematics 2010-09-07 Yuhong Xu

We consider a classical finite horizon optimal control problem for continuous-time pure jump Markov processes described by means of a rate transition measure depending on a control parameter and controlled by a feedback law. For this class…

Probability · Mathematics 2015-01-20 Elena Bandini , Marco Fuhrman