English
Related papers

Related papers: The Deep Learning Galerkin Method for the General …

200 papers

This paper introduces a new weak Galerkin (WG) finite element method for second order elliptic equations on polytopal meshes. This method, called WG-FEM, is designed by using a discrete weak gradient operator applied to discontinuous…

Numerical Analysis · Mathematics 2012-08-20 Lin Mu , Junping Wang , Xiu Ye

We consider Galerkin finite element methods for semilinear stochastic partial differential equations (SPDEs) with multiplicative noise and Lipschitz continuous nonlinearities. We analyze the strong error of convergence for spatially…

Numerical Analysis · Mathematics 2014-11-26 Raphael Kruse

A semi-Lagrangian discontinuous finite element scheme based on the characteristic Galerkin method (CSLDG) is investigated, which directly discretizes an integral invariant model derived from the coupling of the transport equation and its…

Numerical Analysis · Mathematics 2026-05-08 Zhengrong Xie

Deep generative models (DGM) are neural networks with many hidden layers trained to approximate complicated, high-dimensional probability distributions using a large number of samples. When trained successfully, we can use the DGMs to…

Machine Learning · Computer Science 2021-04-13 Lars Ruthotto , Eldad Haber

We present a matrix-free multigrid method for high-order discontinuous Galerkin (DG) finite element methods with GPU acceleration. A performance analysis is conducted, comparing various data and compute layouts. Smoother implementations are…

Numerical Analysis · Mathematics 2025-11-03 Cu Cui , Guido Kanschat

Classical numerical methods for solving partial differential equations suffer from the curse dimensionality mainly due to their reliance on meticulously generated spatio-temporal grids. Inspired by modern deep learning based techniques for…

Machine Learning · Statistics 2018-04-20 Maziar Raissi

This paper introduces a novel staggered discontinuous Galerkin (SDG) method tailored for solving elliptic equations on polytopal meshes. Our approach utilizes a primal-dual grid framework to ensure local conservation of fluxes,…

Numerical Analysis · Mathematics 2024-11-01 L. Chen , X. Huang , E. Park , R. Wang

In this paper, we theoretically and numerically verify that the discontinuous Galerkin (DG) methods with central fluxes for linear hyperbolic equations on non-uniform meshes have sub-optimal convergence properties when measured in the…

Numerical Analysis · Mathematics 2020-03-03 Yong Liu , Chi-Wang Shu , Mengping Zhang

We consider a class of time dependent second order partial differential equations governed by a decaying entropy. The solution usually corresponds to a density distribution, hence positivity (non-negativity) is expected. This class of…

Numerical Analysis · Mathematics 2018-11-28 Zheng Sun , José A. Carrillo , Chi-Wang Shu

Discontinuous Galerkin (dG) methods on meshes consisting of polygonal/polyhedral (henceforth, collectively termed as \emph{polytopic}) elements have received considerable attention in recent years. Due to the physical frame basis functions…

Numerical Analysis · Mathematics 2021-02-16 Zhaonan Dong , Emmanuil H. Georgoulis , Thomas Kappas

We consider spectral mixed discontinuous Galerkin finite element discretizations of the Lam\'e system of linear elasticity in polyhedral domains in $\mathbb{R}^3$. In order to resolve possible corner, edge, and corner-edge singularities,…

Numerical Analysis · Mathematics 2019-08-14 Thomas P. Wihler , Marcel Wirz

This work presents a deep learning-based framework for the solution of partial differential equations on complex computational domains described with computer-aided design tools. To account for the underlying distribution of the training…

Computational Engineering, Finance, and Science · Computer Science 2022-03-18 Moritz von Tresckow , Stefan Kurz , Herbert De Gersem , Dimitrios Loukrezis

The roots of Discontinuous Galerkin (DG) methods is usually attributed to Reed and Hills in a paper published in 1973 on the numerical approximation of the neutron transport equation [18]. In fact, the adventure really started with a rather…

Numerical Analysis · Mathematics 2016-02-16 Adam Larat

A discontinuous Galerkin (DG) scheme for solving semilinear elliptic problem is developed and analyzed in this paper. The DG finite element discretizations are established, and the corresponding existence and uniqueness theorem is proved by…

Numerical Analysis · Mathematics 2021-01-27 Jiajun Zhan , Liuqiang Zhong , Jie Peng

In this paper, we develop a sparse grid discontinuous Galerkin (DG) scheme for transport equations and applied it to kinetic simulations. The method uses the weak formulations of traditional Runge-Kutta DG (RKDG) schemes for hyperbolic…

Numerical Analysis · Mathematics 2016-02-08 Wei Guo , Yingda Cheng

This paper presents a new and efficient numerical algorithm for the biharmonic equation by using weak Galerkin (WG) finite element methods. The WG finite element scheme is based on a variational form of the biharmonic equation that is…

Numerical Analysis · Mathematics 2013-09-24 Chunmei Wang , Junping Wang

We present a new numerical tool for solving the special relativistic ideal MHD equations that is based on the combination of the following three key features: (i) a one-step ADER discontinuous Galerkin (DG) scheme that allows for an…

High Energy Astrophysical Phenomena · Physics 2015-08-12 Olindo Zanotti , Francesco Fambri , Michael Dumbser

We propose two new alternative numerical schemes to solve the coupled Einstein-Euler equations in the Generalized Harmonic formulation. The first one is a finite difference (FD) Central Weighted Essentially Non-Oscillatory (CWENO) scheme on…

Numerical Analysis · Mathematics 2026-05-12 Stefano Muzzolon , Michael Dumbser , Olindo Zanotti , Elena Gaburro

This work focuses on the development of efficient solvers for the pseudo-stress formulation of the unsteady Stokes problem, discretised by means of a discontinuous Galerkin method on polytopal grids (PolyDG). The introduction of the…

Numerical Analysis · Mathematics 2026-02-04 Paola F. Antonietti , Alessandra Cancrini , Gabriele Ciaramella

In this paper, we propose a subspace method based on neural networks for eigenvalue problems with high accuracy and low cost. We first construct a neural network-based orthogonal basis by some deep learning method and dimensionality…

Numerical Analysis · Mathematics 2026-01-21 Xiaoying Dai , Yunying Fan , Zhiqiang Sheng