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Hierarchical Matrix (H-matrix) is an approximation technique which splits a target dense matrix into multiple submatrices, and where a selected portion of submatrices are low-rank approximated. The technique substantially reduces both time…

Mathematical Software · Computer Science 2019-11-04 Rise Ooi , Takeshi Iwashita , Takeshi Fukaya , Akihiro Ida , Rio Yokota

This article considers the extension of two-grid $hp$-version discontinuous Galerkin finite element methods for the numerical approximation of second-order quasilinear elliptic boundary value problems of monotone type to the case when…

Numerical Analysis · Mathematics 2021-12-10 Scott Congreve , Paul Houston

We propose a method to efficiently compute tomographic projections of a 3D volume represented by a linear combination of shifted B-splines. To do so, we propose a ray-tracing algorithm that computes 3D line integrals with arbitrary…

Computer Vision and Pattern Recognition · Computer Science 2025-11-17 Youssef Haouchat , Sepand Kashani , Aleix Boquet-Pujadas , Philippe Thévenaz , Michael Unser

We propose a method for efficient simulations in extended ensembles, useful, e.g., for the study of problems with complex energy landscapes and for free energy calculations. The main difficulty in such simulations is the estimation of the a…

Statistical Mechanics · Physics 2012-05-29 Jack Lidmar

In this paper, we propose a method for the approximation of the solution of high-dimensional weakly coercive problems formulated in tensor spaces using low-rank approximation formats. The method can be seen as a perturbation of a minimal…

Numerical Analysis · Mathematics 2015-02-13 Marie Billaud-Friess , Anthony Nouy , Olivier Zahm

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

The objective of this study is to address the difficulty of simplifying the geometric model in which a differential problem is formulated, also called defeaturing, while simultaneously ensuring that the accuracy of the solution is…

Numerical Analysis · Mathematics 2023-06-09 Jochen Hinz , Ondine Chanon , Alessandra Arrigoni , Annalisa Buffa

In simulation technology, computationally expensive objective functions are often replaced by cheap surrogates, which can be obtained by interpolation. Full grid interpolation methods suffer from the so-called curse of dimensionality,…

Numerical Analysis · Mathematics 2019-10-15 Julian Valentin

Numerical computation of the Karhunen--Lo\`eve expansion is computationally challenging in terms of both memory requirements and computing time. We compare two state-of-the-art methods that claim to efficiently solve for the K--L expansion:…

Computational Engineering, Finance, and Science · Computer Science 2021-01-05 Michal Lukasz Mika , René Rinke Hiemstra , Thomas Joseph Robert Hughes , Dominik Schillinger

Standard Gaussian Process (GP) regression, a powerful machine learning tool, is computationally expensive when it is applied to large datasets, and potentially inaccurate when data points are sparsely distributed in a high-dimensional…

Machine Learning · Computer Science 2016-03-08 Z. Zhang , K. Duraisamy , N. A. Gumerov

We present a geometric multigrid solver based on adaptive smoothed aggregation suitable for Discontinuous Galerkin (DG) discretisations. Mesh hierarchies are formed via domain decomposition techniques, and the method is applicable to fully…

Numerical Analysis · Mathematics 2025-06-02 Yulong Pan , Michael Lindsey , Per-Olof Persson

We present and analyze a new embedded--hybridized discontinuous Galerkin finite element method for the Stokes problem. The method has the attractive properties of full hybridized methods, namely an $H({\rm div})$-conforming velocity field,…

Numerical Analysis · Mathematics 2023-07-06 Sander Rhebergen , Garth N. Wells

We derive and analyze a hybridizable discontinuous Galerkin (HDG) method for approximating weak solutions to the equations of time-harmonic linear elasticity on a bounded Lipschitz domain in three dimensions. The real symmetry of the stress…

Numerical Analysis · Mathematics 2016-11-18 Allan Hungria , Daniele Prada , Francisco-Javier Sayas

The subject of this work is a new stochastic Galerkin method for second-order elliptic partial differential equations with random diffusion coefficients. It combines operator compression in the stochastic variables with tree-based spline…

Numerical Analysis · Mathematics 2022-06-02 Markus Bachmayr , Igor Voulis

This paper presents a novel method for solving partial differential equations on three-dimensional CAD geometries by means of immersed isogeometric discretizations that do not require quadrature schemes. It relies on a new developed…

Numerical Analysis · Mathematics 2021-07-20 Pablo Antolin , Thibaut Hirschler

In the frame of isogeometric analysis, we consider a Galerkin boundary element discretization of the hyper-singular integral equation associated with the 2D Laplacian. We propose and analyze an adaptive algorithm which locally refines the…

Numerical Analysis · Mathematics 2020-03-03 Gregor Gantner , Dirk Praetorius , Stefan Schimanko

In this paper we introduce three complementary three-dimensional weighted quadratic enrichment strategies to improve the accuracy of local histopolation on tetrahedral meshes. The first combines face and interior weighted moments…

Numerical Analysis · Mathematics 2025-11-11 Allal Guessab , Federico Nudo

We introduce a pure--stress formulation of the elasticity eigenvalue problem with mixed boundary conditions. We propose an H(div)-based discontinuous Galerkin method that imposes strongly the symmetry of the stress for the discretization of…

Numerical Analysis · Mathematics 2022-05-06 Salim Meddahi

In this paper we consider spaces of bivariate splines of bi-degree (m, n) with maximal order of smoothness over domains associated to a two-dimensional grid. We define admissible classes of domains for which suitable combinatorial technique…

Computational Geometry · Computer Science 2021-08-18 Dmitry Berdinsky , Tae-wan Kim , Durkbin Cho , Cesare Bracco , Sutipong Kiatpanichgij

We present a class of reduced basis (RB) methods for the iterative solution of parametrized symmetric positive-definite (SPD) linear systems. The essential ingredients are a Galerkin projection of the underlying parametrized system onto a…

Numerical Analysis · Mathematics 2018-04-18 Ngoc-Cuong Nguyen , Yanlai Chen