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Parametric partial differential equations (PDEs) are fundamental for modeling a wide range of physical and engineering systems influenced by uncertain or varying parameters. Traditional neural network-based solvers, such as Physics-Informed…

Machine Learning · Computer Science 2025-12-29 Qiuqi Li , Yiting Liu , Jin Zhao , Wencan Zhu

We solve first-kind Fredholm boundary integral equations arising from Helmholtz and Laplace problems on bounded, smooth screens in three-dimensions with either Dirichlet or Neumann conditions. The proposed Galerkin-Bubnov method takes as…

Numerical Analysis · Mathematics 2020-11-12 Jose Pinto , Carlos Jerez-Hanckes

Real-world fine-tuning of dexterous manipulation policies remains challenging due to limited real-world interaction budgets and highly multimodal action distributions. Diffusion-based policies, while expressive, do not permit conservative…

Robotics · Computer Science 2026-04-07 Chenyu Yang , Denis Tarasov , Davide Liconti , Hehui Zheng , Robert K. Katzschmann

We present a novel high-order accurate nodal discontinuous Galerkin (DG) method for solving nonlinear hyperbolic systems of partial differential equations (PDEs) on fully unstructured three-dimensional polyhedral meshes. A mesh generator is…

Numerical Analysis · Mathematics 2026-05-04 Sixtine Michel , Lorenzo Diazzi , Walter Boscheri

We introduce Discontinuous Galerkin Finite Element Operator Network (DG--FEONet), a data-free operator learning framework that combines the strengths of the discontinuous Galerkin (DG) method with neural networks to solve parametric partial…

Numerical Analysis · Mathematics 2026-01-08 Kapil Chawla , Youngjoon Hong , Jae Yong Lee , Sanghyun Lee

The purpose of the present paper is to compare two semi-Lagrangian methods in the context of the four-dimensional Vlasov--Poisson equation. More specifically, our goal is to compare the performance of the more recently developed…

Numerical Analysis · Mathematics 2018-11-14 Lukas Einkemmer

The discontinuous Galerkin dG method provides a robust and flexible technique for the time integration of fractional diffusion problems. However, a practical implementation uses coefficients defined by integrals that are not easily…

Numerical Analysis · Mathematics 2022-08-09 William McLean

A novel mixed spectral-Galerkin method based on generalized ball polynomials is proposed for solving the biharmonic equation on a unit ball. By introducing an auxiliary variable to decouple the biharmonic equation into a system of…

Numerical Analysis · Mathematics 2026-05-29 Mengxue Gao , Bing Su , Jianwei Zhou

In this paper, we introduce a fast Fourier-Galerkin method for solving boundary integral equations on torus-shaped surfaces, which are diffeomorphic to a torus. We analyze the properties of the integral operator's kernel to derive the decay…

Numerical Analysis · Mathematics 2024-10-10 Yiying Fang , Ying Jiang , Jiafeng Su

In this paper we develop a class of efficient Galerkin boundary element methods for the solution of two-dimensional exterior single-scattering problems. Our approach is based upon construction of Galerkin approximation spaces confined to…

Numerical Analysis · Mathematics 2018-01-16 Fatih Ecevit , Hasan Hüseyin Eruslu

This paper reviews the adaptive sparse grid discontinuous Galerkin (aSG-DG) method for computing high dimensional partial differential equations (PDEs) and its software implementation. The C\texttt{++} software package called AdaM-DG,…

Numerical Analysis · Mathematics 2022-11-04 Juntao Huang , Wei Guo , Yingda Cheng

The discontinuous Galerkin (DG) method is an established method for computing approximate solutions of partial differential equations in many applications. Unlike continuous finite elements, in DG methods, numerical fluxes are used to…

Numerical Analysis · Mathematics 2019-12-02 Kenneth Duru , Leonhard Rannabauer , Alice-Agnes Gabriel , Heiner Igel

In this study, we propose a unified, general framework for the direct discontinuous Galerkin methods. In the new framework, the antiderivative of the nonlinear diffusion matrix is not needed. This allows a simple definition of the numerical…

Numerical Analysis · Mathematics 2022-09-29 Mustafa Engin Danis , Jue Yan

We begin by addressing the time-domain full-waveform inversion using the adjoint method. Next, we derive the scaled boundary semi-weak form of the scalar wave equation in heterogeneous media through the Galerkin method. Unlike conventional…

Numerical Analysis · Mathematics 2025-01-14 Alireza Daneshyar , Stefan Kollmannsberger

The shallow water equations (SWE) are a commonly used model to study tsunamis, tides, and coastal ocean circulation. However, there exist various approaches to discretize and solve them efficiently. Which of them is best for a certain…

Mathematical Software · Computer Science 2019-04-19 Sara Faghih-Naini , Sebastian Kuckuk , Vadym Aizinger , Daniel Zint , Roberto Grosso , Harald Köstler

We present a novel Discontinuous Galerkin Finite Element Method for wave propagation problems. The method employs space-time Trefftz-type basis functions that satisfy the underlying partial differential equations and the respective…

Computational Physics · Physics 2015-05-19 Fritz Kretzschmar , Sascha Schnepp , Igor Tsukerman , Thomas Weiland

We propose and study discontinuous Galerkin methods for strongly degenerate convection-diffusion equations perturbed by a fractional diffusion (L\'evy) operator. We prove various stability estimates along with convergence results toward…

Numerical Analysis · Mathematics 2011-11-29 Simone Cifani , Espen R. Jakobsen , Kenneth H. Karlsen

A Petrov-Galerkin finite element method is constructed for a singularly perturbed elliptic problem in two space dimensions. The solution contains a regular boundary layer and two characteristic boundary layers. Exponential splines are used…

Numerical Analysis · Mathematics 2023-11-02 Alan F. Hegarty , Eugene O'Riordan

Algorithms and underlying mathematics are presented for numerical computation with periodic functions via approximations to machine precision by trigonometric polynomials, including the solution of linear and nonlinear periodic ordinary…

Numerical Analysis · Mathematics 2015-11-03 Grady B. Wright , Mohsin Javed , Hadrien Montanelli , Lloyd N. Trefethen

In this article, a new deep learning architecture, named JDNN, has been proposed to approximate a numerical solution to Partial Differential Equations (PDEs). The JDNN is capable of solving high-dimensional equations. Here, Jacobi Deep…

Numerical Analysis · Mathematics 2022-12-29 Maryam Babaei , Kimia Mohammadi Mohammadi , Zeinab Hajimohammadi , Kourosh Parand
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