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In this work, we develop an efficient solver based on neural networks for second-order elliptic equations with variable coefficients and singular sources. This class of problems covers general point sources, line sources and the combination…

Numerical Analysis · Mathematics 2023-04-18 Tianhao Hu , Bangti Jin , Zhi Zhou

The Neumann--Neumann method is a commonly employed domain decomposition method for linear elliptic equations. However, the method exhibits slow convergence when applied to semilinear equations and does not seem to converge at all for…

Numerical Analysis · Mathematics 2023-12-19 Emil Engström , Eskil Hansen

This article introduces a new primal-dual weak Galerkin (PDWG) finite element method for second order elliptic interface problems with ultra-low regularity assumptions on the exact solution and the interface and boundary data. It is proved…

Numerical Analysis · Mathematics 2020-10-29 Waixiang Cao , Chunmei Wang , Junping Wang

This work is devoted to the development and analysis of a linearization algorithm for microscopic elliptic equations, with scaled degenerate production, posed in a perforated medium and constrained by the homogeneous Neumann-Dirichlet…

Numerical Analysis · Mathematics 2020-08-11 Anh-Khoa Vo , Ekeoma Rowland Ijioma , Nhu-Ngoc Nguyen

We develop a cut Discontinuous Galerkin method (cutDGM) for a diffusion-reaction equation in a bulk domain which is coupled to a corresponding equation on the boundary of the bulk domain. The bulk domain is embedded into a structured,…

Numerical Analysis · Mathematics 2017-07-10 Andre Massing

This paper applies the gradient discretisation method (GDM) for fourth order elliptic variational inequalities. The GDM provides a new formulation of error estimates and a complete convergence analysis of several numerical methods. We show…

Numerical Analysis · Mathematics 2023-05-31 Yahya Alnashri

This paper presents a hybridized formulation for the weak Galerkin mixed finite element method (WG-MFEM) which was introduced and analyzed for second order elliptic equations. The WG-MFEM method was designed by using discontinuous piecewise…

Numerical Analysis · Mathematics 2015-08-25 Lin Mu , Junping Wang , Xiu Ye

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

This paper develops interior penalty discontinuous Galerkin (IP-DG) methods to approximate $W^{2,p}$ strong solutions of second order linear elliptic partial differential equations (PDEs) in non-divergence form with continuous coefficients.…

Numerical Analysis · Mathematics 2016-05-17 Xiaobing Feng , Michael Neilan , Stefan Schnake

A modified primal-dual weak Galerkin (M-PDWG) finite element method is designed for the second order elliptic equation in non-divergence form. Compared with the existing PDWG methods proposed in \cite{wwnondiv}, the system of equations…

Numerical Analysis · Mathematics 2020-11-24 Chunmei Wang

We introduce a generalized finite difference method for solving a large range of fully nonlinear elliptic partial differential equations in three dimensions. Methods are based on Cartesian grids, augmented by additional points carefully…

Numerical Analysis · Mathematics 2021-03-19 Brittany Froese Hamfeldt , Jacob Lesniewski

The embedded discontinuous Galerkin (EDG) method by Cockburn et al. [SIAM J. Numer. Anal., 2009, 47(4), 2686-2707] is obtained from the hybridizable discontinuous Galerkin method by changing the space of the Lagrangian multiplier from…

Numerical Analysis · Mathematics 2017-11-16 Xiao Zhang , Xiaoping Xie , Shiquan Zhang

In this paper, we discuss the second-order finite element method (FEM) and finite difference method (FDM) for numerically solving elliptic cross-interface problems characterized by vertical and horizontal straight lines, piecewise constant…

Numerical Analysis · Mathematics 2024-11-04 Qiwei Feng

With recent advancements in computer hardware and software platforms, there has been a surge of interest in solving partial differential equations with deep learning-based methods, and the integration with domain decomposition strategies…

Numerical Analysis · Mathematics 2023-05-18 Qi Sun , Xuejun Xu , Haotian Yi

In this paper we propose a finite element method for solving elliptic equations with the observational Dirichlet boundary data which may subject to random noises. The method is based on the weak formulation of Lagrangian multiplier. We show…

Numerical Analysis · Mathematics 2017-02-20 Zhiming Chen , Rui Tuo , Wenlong Zhang

A full multigrid finite element method is proposed for semilinear elliptic equations. The main idea is to transform the solution of the semilinear problem into a series of solutions of the corresponding linear boundary value problems on the…

Numerical Analysis · Mathematics 2017-03-29 Hehu Xie , Fei Xu

We extend the Deep Galerkin Method (DGM) introduced in Sirignano and Spiliopoulos (2018)} to solve a number of partial differential equations (PDEs) that arise in the context of optimal stochastic control and mean field games. First, we…

Computational Finance · Quantitative Finance 2022-04-20 Ali Al-Aradi , Adolfo Correia , Danilo de Frietas Naiff , Gabriel Jardim , Yuri Saporito

We propose Dirichlet Process mixtures of Generalized Linear Models (DP-GLM), a new method of nonparametric regression that accommodates continuous and categorical inputs, and responses that can be modeled by a generalized linear model. We…

Machine Learning · Statistics 2010-07-16 Lauren A. Hannah , David M. Blei , Warren B. Powell

The matched interface and boundary (MIB) method has a proven ability for delivering the second order accuracy in handling elliptic interface problems with arbitrarily complex interface geometries. However, its collocation formulation…

Numerical Analysis · Mathematics 2015-09-04 Yin Cao , Bao Wang , Kelin Xia , Guowi Wei

Deep neural networks are powerful tools for approximating functions, and they are applied to successfully solve various problems in many fields. In this paper, we propose a neural network-based numerical method to solve partial differential…

Numerical Analysis · Mathematics 2022-02-01 Yong Shang , Fei Wang , Jingbo Sun
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