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Related papers: Multiscale-Spectral GFEM and Optimal Oversampling

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In this paper, we present a finite element method (FEM) framework enhanced by an operator-adapted wavelet decomposition algorithm designed for the efficient analysis of multiscale electromagnetic problems. Usual adaptive FEM approaches,…

Computational Physics · Physics 2026-02-18 F. Şık , F. L. Teixeira , B. Shanker

Identifying the underlying models in a set of data points contaminated by noise and outliers, leads to a highly complex multi-model fitting problem. This problem can be posed as a clustering problem by the projection of higher order…

Computer Vision and Pattern Recognition · Computer Science 2018-08-01 Ruwan Tennakoon , Alireza Sadri , Reza Hoseinnezhad , Alireza Bab-Hadiashar

We present a hybrid numerical-asymptotic (HNA) boundary element method (BEM) for high frequency scattering by two-dimensional screens and apertures, whose computational cost to achieve any prescribed accuracy remains bounded with increasing…

Numerical Analysis · Mathematics 2020-04-03 Andrew Gibbs , David Hewett , Daan Huybrechs , Emile Parolin

We develop a new spatial semidiscrete multiscale method based upon the edge multiscale methods to solve semilinear parabolic problems with heterogeneous coefficients and smooth initial data. This method allows for a cheap spatial…

Numerical Analysis · Mathematics 2025-12-16 Leonardo A. Poveda , Shubin Fu , Guanglian Li , Eric Chung

In this paper, we consider the quasi-gas-dynamic (QGD) model in a multiscale environment. The model equations can be regarded as a hyperbolic regularization and are derived from kinetic equations. So far, the research on QGD models has been…

Numerical Analysis · Mathematics 2021-06-30 Boris Chetverushkin , Eric Chung , Yalchin Efendiev , Sai-Mang Pun , Zecheng Zhang

A valuable step in the modeling of multiscale dynamical systems in fields such as computational chemistry, biology, materials science and more, is the representative sampling of the phase space over long timescales of interest; this task is…

Machine Learning · Computer Science 2023-12-29 Ellis R. Crabtree , Juan M. Bello-Rivas , Ioannis G. Kevrekidis

The construction of local reduced-order models via multiscale basis functions has been an area of active research. In this paper, we propose online multiscale basis functions which are constructed using the offline space and the current…

Numerical Analysis · Mathematics 2015-01-20 Eric T. Chung , Yalchin Efendiev , Wing Tat Leung

Multidimensional scaling (MDS) is a family of methods that embed a given set of points into a simple, usually flat, domain. The points are assumed to be sampled from some metric space, and the mapping attempts to preserve the distances…

Computational Geometry · Computer Science 2014-03-05 Yonathan Aflalo , Anastasia Dubrovina , Ron Kimmel

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

This paper presents an asymptotically compatible error bound for the finite element method (FEM) applied to a nonlocal diffusion model. The analysis covers two scenarios: meshes with and without shape regularity. For shape-regular meshes,…

Numerical Analysis · Mathematics 2025-06-06 Yanzun Meng , Zuoqiang Shi

Spectral element methods (SEM), which are extensions of finite element methods (FEM), are important emerging techniques for solving partial differential equations in physics and engineering. SEM can potentially deliver better accuracy due…

Numerical Analysis · Mathematics 2023-04-28 Jacob Jones , Rebecca Conley , Xiangmin Jiao

We present a computational framework for efficient optimization-based "inverse design" of large-area "metasurfaces" (subwavelength-patterned surfaces) for applications such as multi-wavelength and multi-angle optimizations, and…

In this work, we propose two different approaches to improve the semantic consistency of Open Set Semantic Segmentation. First, we propose a method called OpenGMM that extends the OpenPCS framework using a Gaussian Mixture of Models to…

Computer Vision and Pattern Recognition · Computer Science 2022-06-07 Ian Nunes , Matheus B. Pereira , Hugo Oliveira , Jefersson A. Dos Santos , Marcus Poggi

A new methodology for the improvement of the performance of inexpensive static passive electromagnetic skins (SP-EMSs) is presented. The proposed approach leverages on the non-uniqueness of the inverse source problem associated to the…

Systems and Control · Electrical Eng. & Systems 2024-08-14 Giacomo Oliveri , Francesco Zardi , Andrea Massa

In this paper, we consider a poroelasticity problem in heterogeneous multicontinuum media that is widely used in simulations of the unconventional hydrocarbon reservoirs and geothermal fields. Mathematical model contains a coupled system of…

Numerical Analysis · Mathematics 2019-08-07 Aleksei Tyrylgin , Maria Vasilyeva , Denis Spiridonov , Eric T. Chung

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

In this paper, we demonstrate the construction of generalized Rough Polyhamronic Splines (GRPS) within the Bayesian framework, in particular, for multiscale PDEs with rough coefficients. The optimal coarse basis can be derived automatically…

Numerical Analysis · Mathematics 2021-03-03 Xinliang Liu , Lei Zhang , Shengxin Zhu

A method to design gratings in integrated photonics, is presented. The method is based on a transfer matrix formalism enhanced by Finite Element Method (FEM) parameter calculations. The main advantages of the proposed technique are the easy…

Optics · Physics 2021-06-14 Clara Zaccaria , Mattia Mancinelli , Lorenzo Pavesi

We take a new look at parameter estimation for Gaussian Mixture Models (GMMs). In particular, we propose using \emph{Riemannian manifold optimization} as a powerful counterpart to Expectation Maximization (EM). An out-of-the-box invocation…

Machine Learning · Statistics 2015-06-26 Reshad Hosseini , Suvrit Sra

A numerical scheme is presented for approximating fractional order Poisson problems in two and three dimensions. The scheme is based on reformulating the original problem posed over $\Omega$ on the extruded domain…

Numerical Analysis · Mathematics 2019-05-27 Mark Ainsworth , Christian Glusa