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We extend the results of the FBSDE theory in order to construct a probabilistic representation of a viscosity solution to the Cauchy problem for a system of quasilinear parabolic equations. We derive a BSDE associated with a class of…

Probability · Mathematics 2016-06-09 Ya. I. Belopolskaya

Motivated by applications to the dynamic control of queueing networks, we develop a simulation-based scheme, the so-called multilevel Picard (MLP) approximation, for solving high-dimensional drift control problems whose states are…

Optimization and Control · Mathematics 2025-10-27 Yuan Zhong

We introduce a notion of approximate viscosity solution for a class of nonlinear path-dependent PDEs (PPDEs), including the Hamilton-Jacobi-Bellman type equations. Existence, comparaison and stability results are established under fairly…

Analysis of PDEs · Mathematics 2021-09-09 Bruno Bouchard , Grégoire Loeper , Xiaolu Tan

The aim of the present work is the introduction of a viscosity type solution, called strong-viscosity solution to distinguish it from the classical one, with the following peculiarities: it is a purely analytic object; it can be easily…

Probability · Mathematics 2019-03-19 Andrea Cosso , Francesco Russo

A high-frequency recovered fully discrete low-regularity integrator is constructed to approximate rough and possibly discontinuous solutions of the semilinear wave equation. The proposed method, with high-frequency recovery techniques, can…

Numerical Analysis · Mathematics 2024-10-18 Jiachuan Cao , Buyang Li , Yanping Lin , Fangyan Yao

We present a deep learning algorithm for the numerical solution of parametric families of high-dimensional linear Kolmogorov partial differential equations (PDEs). Our method is based on reformulating the numerical approximation of a whole…

Machine Learning · Computer Science 2021-05-11 Julius Berner , Markus Dablander , Philipp Grohs

In this note we shall introduce a simple, effective numerical method for solving partial differential equations for scalar and vector-valued data defined on surfaces. Even though we shall follow the traditional way to approximate the…

Computational Geometry · Computer Science 2009-07-13 Sheng-Gwo Chen , Mei-Hsiu Chi , Jyh-Yang Wu

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

For the fractional Laplacian of variable order, an efficient and accurate numerical evaluation in multi-dimension is a challenge for the nature of a singular integral. We propose a simple and easy-to-implement finite difference scheme for…

Numerical Analysis · Mathematics 2024-06-18 Zhaopeng Hao , Siyuan Shi , Zhongqiang Zhang , Rui Du

In this paper, we present a deep learning-based numerical method for approximating high dimensional stochastic partial differential equations (SPDEs). At each time step, our method relies on a predictor-corrector procedure. More precisely,…

Numerical Analysis · Mathematics 2022-09-13 He Zhang , Ran Zhang , Tao Zhou

We introduce a method-of-lines formulation of the closest point method, a numerical technique for solving partial differential equations (PDEs) defined on surfaces. This is an embedding method, which uses an implicit representation of the…

Numerical Analysis · Mathematics 2013-07-23 Ingrid von Glehn , Thomas März , Colin B. Macdonald

Quasi-Monte Carlo (QMC) methods are applied to multi-level Finite Element (FE) discretizations of elliptic partial differential equations (PDEs) with a random coefficient, to estimate expected values of linear functionals of the solution.…

Numerical Analysis · Mathematics 2014-05-16 Frances Y. Kuo , Christoph Schwab , Ian H. Sloan

We apply the semi-discrete method, c.f. \emph{N. Halidias and I.S. Stamatiou (2016), On the numerical solution of some non-linear stochastic differential equations using the semi-discrete method, Computational Methods in Applied…

Numerical Analysis · Mathematics 2018-07-25 Ioannis S. Stamatiou

Simulations of the dynamics generated by partial differential equations (PDEs) provide approximate, numerical solutions to initial value problems. Such simulations are ubiquitous in scientific computing, but the correctness of the results…

Numerical Analysis · Mathematics 2026-01-09 Jan Bouwe van den Berg , Maxime Breden

Neural operators serve as universal approximators for general continuous operators. In this paper, we derive the approximation rate of solution operators for the nonlinear parabolic partial differential equations (PDEs), contributing to the…

Machine Learning · Computer Science 2024-10-04 Takashi Furuya , Koichi Taniguchi , Satoshi Okuda

Recently, it has been great interest in the development of methods for solving nonlinear differential equations directly. Here, it is shown an algorithm based on Pad\'e approximants for solving nonlinear partial differential equations…

Mathematical Physics · Physics 2015-01-28 Danilo V. Ruy

The multiscale complexity of modern problems in computational science and engineering can prohibit the use of traditional numerical methods in multi-dimensional simulations. Therefore, novel algorithms are required in these situations to…

Numerical Analysis · Mathematics 2021-06-15 Cale Harnish , Luke Dalessandro , Karel Matous , Daniel Livescu

We study iterative finite element approximations for the numerical approximation of semilinear elliptic boundary value problems with monotone nonlinear reactions of subcritical growth. The focus of our contribution is on an optimal a priori…

Numerical Analysis · Mathematics 2025-08-18 Florian Spicher , Thomas P. Wihler

We prove convergence with optimal algebraic rates for an adaptive finite element method for nonlinear equations with strongly monotone operator. Unlike prior works, our analysis also includes the iterative and inexact solution of the…

Numerical Analysis · Mathematics 2018-11-27 Gregor Gantner , Alexander Haberl , Dirk Praetorius , Bernhard Stiftner

We provide a representation formula for viscosity solutions to a class of nonlinear second order parabolic PDEs given as a sup--envelope function. This is done through a dynamic programming principle derived from Denis, Hu, Peng (2010). The…

Analysis of PDEs · Mathematics 2021-06-23 Marco Pozza
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