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This paper addresses a multi-scale finite element method for second order linear elliptic equations with arbitrarily rough coefficient. We propose a local oversampling method to construct basis functions that have optimal local…

Numerical Analysis · Mathematics 2015-08-04 Thomas Y. Hou , Pengfei Liu

We solve elliptic systems of equations posed on highly heterogeneous materials. Examples of this class of problems are composite structures and geological processes. We focus on a model problem which is a second-order elliptic equation with…

Numerical Analysis · Mathematics 2015-12-11 Leonardo A. Poveda , Sebastian Huepo , Victor M. Calo , Juan Galvis

In this article, we analyse the domain mapping method approach to approximate statistical moments of solutions to linear elliptic partial differential equations posed over random geometries including smooth surfaces and bulk-surface…

Numerical Analysis · Mathematics 2019-03-18 Lewis Church , Ana Djurdjevac , Charles M. Elliott

We consider a randomised implementation of the finite element method (FEM) for elliptic partial differential equations on high-dimensional models. This is motivated by applications where model predictions are essential for real-time process…

Numerical Analysis · Mathematics 2019-07-30 Yue Wu , Dimitris Kamilis , Nick Polydorides

We address multiscale elliptic problems with random coefficients that are a perturbation of multiscale deterministic problems. Our approach consists in taking benefit of the perturbative context to suitably modify the classical Finite…

Numerical Analysis · Mathematics 2011-11-08 C. Le Bris , F. Legoll , F. Thomines

We describe a numerical framework that uses random sampling to efficiently capture low-rank local solution spaces of multiscale PDE problems arising in domain decomposition. In contrast to existing techniques, our method does not rely on…

Numerical Analysis · Mathematics 2020-02-06 Ke Chen , Qin Li , Jianfeng Lu , Stephen J. Wright

This work is concerned with the rigorous analysis on the Generalized Multiscale Finite Element Methods (GMsFEMs) for elliptic problems with high-contrast heterogeneous coefficients. GMsFEMs are popular numerical methods for solving flow…

Numerical Analysis · Mathematics 2018-02-27 Guanglian Li

This paper presents a novel multi-scale method for elliptic partial differential equations with arbitrarily rough coefficients. In the spirit of numerical homogenization, the method constructs problem-adapted ansatz spaces with uniform…

Numerical Analysis · Mathematics 2024-08-05 Philip Freese , Moritz Hauck , Tim Keil , Daniel Peterseim

In this paper, we construct a class of Mixed Generalized Multiscale Finite Element Methods for the approximation on a coarse grid for an elliptic problem in thin two-dimensional domains. We consider the elliptic equation with homogeneous…

Numerical Analysis · Mathematics 2021-10-13 Denis Spiridonov , Maria Vasilyeva , Min Wang , Eric T. Chung

A numerical procedure providing guaranteed two-sided bounds on the effective coefficients of elliptic partial differential operators is presented. The upper bounds are obtained in a standard manner through the variational formulation of the…

Numerical Analysis · Mathematics 2023-07-24 Liya Gaynutdinova , Martin Ladecký , Aleš Nekvinda , Ivana Pultarová , Jan Zeman

We consider a sketched implementation of the finite element method for elliptic partial differential equations on high-dimensional models. Motivated by applications in real-time simulation and prediction we propose an algorithm that…

Numerical Analysis · Mathematics 2020-04-22 Robert Lung , Yue Wu , Dimitris Kamilis , Nick Polydorides

The implementation of the finite element method for linear elliptic equations requires to assemble the stiffness matrix and the load vector. In general, the entries of this matrix-vector system are not known explicitly but need to be…

Numerical Analysis · Mathematics 2019-08-26 Raphael Kruse , Nick Polydorides , Yue Wu

We develop and analyze stochastic inexact Gauss-Newton methods for nonlinear least-squares problems and for nonlinear systems ofequations. Random models are formed using suitable sampling strategies for the matrices involved in the…

Optimization and Control · Mathematics 2024-12-10 Stefania Bellavia , Greta Malaspina , Benedetta Morini

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

Let us assume that $f$ is a continuous function defined on the unit ball of $\mathbb R^d$, of the form $f(x) = g (A x)$, where $A$ is a $k \times d$ matrix and $g$ is a function of $k$ variables for $k \ll d$. We are given a budget $m \in…

Numerical Analysis · Mathematics 2012-01-18 Massimo Fornasier , Karin Schnass , Jan Vybiral

We propose a framework for computing, optimizing and integrating with respect to a smooth marginal likelihood in statistical models that involve high-dimensional parameters/latent variables and continuous low-dimensional hyperparameters.…

Methodology · Statistics 2026-02-10 Omiros Papaspiliopoulos , Timothée Stumpf-Fétizon , Jonathan Weare

Multiple generalized additive models (GAMs) are a type of distributional regression wherein parameters of probability distributions depend on predictors through smooth functions, with selection of the degree of smoothness via $L_2$…

Machine Learning · Statistics 2018-09-26 Yousra El-Bachir , Anthony C. Davison

We construct and analyze a multiscale finite element method for an elliptic distributed optimal control problem with pointwise control constraints, where the state equation has rough coefficients. We show that the performance of the…

Numerical Analysis · Mathematics 2023-09-29 Susanne C. Brenner , Jose C. Garay , Li-yeng Sung

In this paper, we study the development of efficient multiscale methods for flows in heterogeneous media. Our approach uses the Generalized Multiscale Finite Element (GMsFEM) framework. The main idea of GMsFEM is to approximate the solution…

Numerical Analysis · Mathematics 2014-09-26 Victor M. Calo , Y. Efendiev , Juan Galvis , Guanglian Li

The subject of this work is an adaptive stochastic Galerkin finite element method for parametric or random elliptic partial differential equations, which generates sparse product polynomial expansions with respect to the parametric…

Numerical Analysis · Mathematics 2025-03-28 Markus Bachmayr , Martin Eigel , Henrik Eisenmann , Igor Voulis
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