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In many applications it is important to be able to sample paths of SDEs conditional on observations of various kinds. This paper studies SPDEs which solve such sampling problems. The SPDE may be viewed as an infinite dimensional analogue of…

Probability · Mathematics 2010-05-27 M. Hairer , A. M. Stuart , J. Voss , P. Wiberg

In this paper we study the optimal stochastic control problem for a path-dependent stochastic system under a recursive path-dependent cost functional, whose associated Bellman equation from dynamic programming principle is a path-dependent…

Optimization and Control · Mathematics 2013-03-06 Shanjian Tang , Fu Zhang

We establish a comparison principle for viscosity solutions of a class of nonlinear partial differential equations posed on the space of nonnegative finite measures, thereby extending recent results for PDEs defined on the Wasserstein space…

Probability · Mathematics 2026-05-05 Ibrahim Ekren , Xihao He , Tianxu Lan , Xiaolu Tan

In this work, we consider the interaction of a 3D incompressible fluid with a 2D flexible shell that occupies (a part of) the boundary of the fluid domain. We assume that the shell is perfectly elastic while the fluid is governed by the…

Analysis of PDEs · Mathematics 2026-05-15 Dominic Breit , Prince Romeo Mensah , Sebastian Schwarzacher , Pei Su

In this paper we study the relationship between functional forward-backward stochastic systems and path-dependent PDEs. In the framework of functional It\^o calculus, we introduce a path-dependent PDE and prove that its solution is uniquely…

Probability · Mathematics 2012-04-18 Shaolin Ji , Shuzhen Yang

Developing algorithms for solving high-dimensional partial differential equations (PDEs) has been an exceedingly difficult task for a long time, due to the notoriously difficult problem known as the "curse of dimensionality". This paper…

Numerical Analysis · Mathematics 2020-07-17 Jiequn Han , Arnulf Jentzen , Weinan E

Stochastic port-Hamiltonian systems on infinite-dimensional spaces governed by It\^o stochastic differential equations (SDEs) are introduced and some properties of this new class of systems are studied. They are an extension of stochastic…

Optimization and Control · Mathematics 2019-07-10 François Lamoline , Joseph J. Winkin

The nonhomogeneous Navier-Stokes equations with density-dependent viscosity is studied in three-dimensional (3D) exterior domains with nonslip or slip boundary conditions. We prove that the strong solutions exists globally in time provided…

Analysis of PDEs · Mathematics 2022-05-13 Guocai Cai , Boqiang Lü , Yi Peng

In this paper, we establish a new uniqueness result of a (continuous) viscosity solution for some integro-partial differential equation (IPDE in short). The novelty is that we relax the so-called monotonicity assumption on the driver,…

Analysis of PDEs · Mathematics 2015-05-12 Marie-Amélie Morlais , Said Hamadène

We introduce a notion of duality solution for a single or a system of transport equations in spaces of probability measures reminiscent of the viscosity solution notion for nonlinear parabolic equations. Our notion of solution by duality…

Analysis of PDEs · Mathematics 2024-06-05 José A. Carrillo , David Gómez-Castro

Rough stochastic differential equations (rough SDEs), recently introduced by Friz, Hocquet and L\^e in arXiv:2106.10340, have emerged as a versatile tool to study "doubly" SDEs under partial conditioning (with motivation from pathwise…

Probability · Mathematics 2025-07-24 Fabio Bugini , Peter K. Friz , Wilhelm Stannat

We review the construction and analysis of numerical methods for strongly nonlinear PDEs, with an emphasis on convex and nonconvex fully nonlinear equations and the convergence to viscosity solutions. We begin by describing a fundamental…

Numerical Analysis · Mathematics 2016-10-26 Michael Neilan , Abner J. Salgado , Wujun Zhang

This paper extends the results of Ma, Wu, Zhang, Zhang [11] to the context of path-dependent multidimensional forward-backward stochastic differential equations (FBSDE). By path-dependent we mean that the coefficients of the…

Probability · Mathematics 2022-01-14 Kaitong Hu , Zhenjie Ren , Nizar Touzi

The numerical solution of large-scale PDEs, such as those occurring in data-driven applications, unavoidably require powerful parallel computers and tailored parallel algorithms to make the best possible use of them. In fact, considerations…

Numerical Analysis · Mathematics 2017-05-11 Francisco Bernal , Gonçalo dos Reis , Greig Smith

We study stochastic delay differential equations (SDDE) where the coefficients depend on the moving averages of the state process. As a first contribution, we provide sufficient conditions under which a linear path functional of the…

Probability · Mathematics 2013-10-17 Salvatore Federico , Peter Tankov

Solving partial differential equations (PDEs) within the framework of probabilistic numerics offers a principled approach to quantifying epistemic uncertainty arising from discretization. By leveraging Gaussian process regression and…

Machine Learning · Statistics 2025-08-18 Akshay Thakur , Sawan Kumar , Matthew Zahr , Souvik Chakraborty

This paper investigates solution strategies for nonlinear problems in Hilbert spaces, such as nonlinear partial differential equations (PDEs) in Sobolev spaces, when only finite measurements are available. We formulate this as a nonlinear…

Numerical Analysis · Mathematics 2025-06-06 Daozhe Lin , Qiang Du

The integral equation approach to partial differential equations (PDEs) provides significant advantages in the numerical solution of the incompressible Navier-Stokes equations. In particular, the divergence-free condition and boundary…

Numerical Analysis · Mathematics 2020-02-26 Ludvig af Klinteberg , Travis Askham , Mary Catherine Kropinski

In this paper, we consider an incompressible viscous flow without surface tension in a finite-depth domain of three dimensions, with free top boundary and fixed bottom boundary. This system is governed by a Naiver-Stokes equation in above…

Analysis of PDEs · Mathematics 2012-12-11 Lei Wu

The elliptic 2-Hessian equation is a fully nonlinear partial differential equation (PDE) that is related to intrinsic curvature for three dimensional manifolds. We introduce two numerical methods for this PDE: the first is provably…

Numerical Analysis · Mathematics 2016-02-11 Brittany D. Froese , Adam M. Oberman , Tiago Salvador