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We investigate mathematically a nonlinear approximation type approach recently introduced in [A. Ammar et al., J. Non-Newtonian Fluid Mech., 2006] to solve high dimensional partial differential equations. We show the link between the…

Numerical Analysis · Mathematics 2008-11-05 C. Le Bris , T. Lelievre , Y. Maday

We show that degenerate nonlinear diffusion equations can be asymptotically obtained as a limit from a class of nonlocal partial differential equations. The nonlocal equations are obtained as gradient flows of interaction-like energies…

Analysis of PDEs · Mathematics 2023-10-12 José Antonio Carrillo , Antonio Esposito , Jeremy Sheung-Him Wu

The non-linear sewing lemma constructs flows of rough differential equations from a braod class of approximations called almost flows. We consider a class of almost flows that could be approximated by solutions of ordinary differential…

Classical Analysis and ODEs · Mathematics 2021-12-17 Antoine Lejay

A functional differential equation related to the logistic equation is studied by a combination of numerical and perturbation methods. Parameter regions are identified where the solution to the nonlinear problem is approximated well by…

Classical Analysis and ODEs · Mathematics 2026-03-24 Nicholas Hale , Enrique Thomann , JAC Weideman

Motivated by recent work on approximation of diffusion equations by deterministic interacting particle systems, we develop a nonlocal approximation for a range of linear and nonlinear diffusion equations and prove convergence of the method…

Analysis of PDEs · Mathematics 2024-04-05 Katy Craig , Matt Jacobs , Olga Turanova

We develop theory for nonlinear dimensionality reduction (NLDR). A number of NLDR methods have been developed, but there is limited understanding of how these methods work and the relationships between them. There is limited basis for using…

Machine Learning · Statistics 2018-03-08 Daniel Ting , Michael I. Jordan

In this work, an efficient approximation scheme has been proposed for getting accurate approximate solution of nonlinear partial differential equations with constant or variable coefficients satisfying initial conditions in a series of…

Analysis of PDEs · Mathematics 2020-09-04 Prakash Kumar Das , M. M. Panja

This study presents a method for constructing a sequence of approximate solutions of increasing accuracy to general equilibrium models on nonlocal domains. The method is based on a technique originated from dynamical systems theory. The…

Economics · Quantitative Finance 2015-06-16 Viktors Ajevskis

A multiscale numerical method is proposed for the solution of semi-linear elliptic stochastic partial differential equations with localized uncertainties and non-linearities, the uncertainties being modeled by a set of random parameters. It…

Numerical Analysis · Mathematics 2019-01-23 Anthony Nouy , Florent Pled

Approximating functions by a linear span of truncated basis sets is a standard procedure for the numerical solution of differential and integral equations. Commonly used concepts of approximation methods are well-posed and convergent, by…

Numerical Analysis · Mathematics 2022-12-14 Yahya Saleh , Armin Iske , Andrey Yachmenev , Jochen Küpper

Mathematical modeling of many physical processes such as diffusion, viscosity of fluids and combustion involves differential equations with small coefficients of higher derivatives. These may be small diffusion coefficients for modeling the…

Numerical Analysis · Mathematics 2010-02-16 Liudmila Rozanova

We study approximation of non-autonomous linear differential equations with variable delay over infinite intervals. We use piecewise constant argument to obtain a corresponding discrete difference equation. The study of numerical…

Classical Analysis and ODEs · Mathematics 2016-07-26 Daniel Sepúlveda

This paper introduces a new method for semi-supervised learning on high dimensional nonlinear manifolds, which includes a phase of unsupervised basis learning and a phase of supervised function learning. The learned bases provide a set of…

Machine Learning · Statistics 2009-06-30 Kai Yu , Tong Zhang

We present a novel deep learning approach to approximate the solution of large, sparse, symmetric, positive-definite linear systems of equations. These systems arise from many problems in applied science, e.g., in numerical methods for…

Machine Learning · Computer Science 2022-10-04 Ayano Kaneda , Osman Akar , Jingyu Chen , Victoria Kala , David Hyde , Joseph Teran

Given a function dictionary $\cal D$ and an approximation budget $N\in\mathbb{N}^+$, nonlinear approximation seeks the linear combination of the best $N$ terms $\{T_n\}_{1\le n\le N}\subseteq{\cal D}$ to approximate a given function $f$…

Machine Learning · Computer Science 2020-11-06 Zuowei Shen , Haizhao Yang , Shijun Zhang

In the context of data-driven control of nonlinear systems, many approaches lack of rigorous guarantees, call for nonconvex optimization, or require knowledge of a function basis containing the system dynamics. To tackle these drawbacks, we…

Systems and Control · Electrical Eng. & Systems 2023-10-05 Tim Martin , Frank Allgöwer

This chapter describes how gradient flows and nonlinear power methods in Banach spaces can be used to solve nonlinear eigenvector-dependent eigenvalue problems, and how convergence of (discretized) approximations can be verified. We review…

Numerical Analysis · Mathematics 2022-03-15 Leon Bungert , Martin Burger

In the paper titled "New numerical approach for fractional differential equations" by A. Atangana and K.M. Owolabi [Math. Model. Nat. Phenom., 13(1), 2018], it is presented a method for the numerical solution of some fractional differential…

Numerical Analysis · Mathematics 2019-02-27 Roberto Garrappa

In this paper we present a numerical scheme for nonlinear continuity equations, which is based on the gradient flow formulation of an energy functional with respect to the quadratic transportation distance. It can be applied to a large…

Numerical Analysis · Mathematics 2016-11-23 José A. Carrillo , Helene Ranetbauer , Marie-Therese Wolfram

The aim of this work is to establish numerous interrelated gradient estimates in the nonlinear nonlocal setting. First of all, we prove that weak solutions to a class of homogeneous nonlinear nonlocal equations of possibly arbitrarily low…

Analysis of PDEs · Mathematics 2024-08-09 Lars Diening , Kyeongbae Kim , Ho-Sik Lee , Simon Nowak
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