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In this article we investigate the existence of a solution to a semilinear, elliptic, partial differential equation with distributional coefficients and data. The problem we consider is a generalization of the Lichnerowicz equation that one…

Analysis of PDEs · Mathematics 2013-03-20 Michael Holst , Caleb Meier

In the present study, we consider the Extra-Membrane-Intra model (EMI) for the simulation of excitable tissues at the cellular level. We provide the (possibly large) system of partial differential equations (PDEs), equipped with ad hoc…

Numerical Analysis · Mathematics 2024-09-23 Pietro Benedusi , Paola Ferrari , Marius Causemann , Stefano Serra-Capizzano

Solving parametric partial differential equations (PDEs) presents significant challenges for data-driven methods due to the sensitivity of spatio-temporal dynamics to variations in PDE parameters. Machine learning approaches often struggle…

Machine Learning · Computer Science 2024-11-11 Armand Kassaï Koupaï , Jorge Mifsut Benet , Yuan Yin , Jean-Noël Vittaut , Patrick Gallinari

In this paper, we study a generalized finite element method for solving second-order elliptic partial differential equations with rough coefficients. The method uses local approximation spaces computed by solving eigenvalue problems on…

Numerical Analysis · Mathematics 2025-07-17 Christian Alber , Peter Bastian , Moritz Hauck , Robert Scheichl

This paper is concerned with using discontinuous Galerkin isogeometric analysis (dGIGA) as a numerical treatment of Diffusion problems on orientable surfaces $\Omega \subset \mathbb{R}^3$. The computational domain or surface considered…

Numerical Analysis · Mathematics 2019-04-05 Stephen Edward Moore

Data driven discovery of partial differential equations (PDEs) is a promising approach for uncovering the underlying laws governing complex systems. However, purely data driven techniques face the dilemma of balancing search space with…

Machine Learning · Computer Science 2025-05-12 Hao Xu , Yuntian Chen , Rui Cao , Tianning Tang , Mengge Du , Jian Li , Adrian H. Callaghan , Dongxiao Zhang

In this study, a new coupled Partial Differential Equation (CPDE) based image denoising model incorporating space-time regularization into non-linear diffusion is proposed. This proposed model is fitted with additive Gaussian noise which…

Numerical Analysis · Mathematics 2019-08-08 Subit K. Jain , Sudeb Majee , Rajendra K. Ray , Ananta K. Majee

Partial differential equation (PDE)-governed inverse problems are fundamental across various scientific and engineering applications; yet they face significant challenges due to nonlinearity, ill-posedness, and sensitivity to noise. Here,…

Machine Learning · Computer Science 2026-03-03 Siming Shan , Min Zhu , Youzuo Lin , Lu Lu

A new diffuse interface model has been proposed in this study for simulating binary alloy solidification under universal cooling conditions, involving both equilibrium and non-equilibrium solute partitioning. Starting from the Gibbs-Thomson…

Materials Science · Physics 2023-09-22 Chuanqi Zhu , Yusuke Seguchi , Masayuki Okugawa , Yuichiro Koizumi

Although Galerkin discretizations have been intensively employed in the IgA context, an efficient implementation requires special numerical quadrature rules when constructing the system of equations. To avoid this issue, isogeometric…

Numerical Analysis · Mathematics 2017-11-30 Fabio Roman

In this paper we present PDE and finite element analyses for a system of partial differential equations (PDEs) consisting of the Darcy equation and the Cahn-Hilliard equation, which arises as a diffuse interface model for the two phase…

Numerical Analysis · Mathematics 2013-04-26 Xiaobing Feng , Steven Wise

We introduce a simple, rigorous, and unified framework for solving nonlinear partial differential equations (PDEs), and for solving inverse problems (IPs) involving the identification of parameters in PDEs, using the framework of Gaussian…

Numerical Analysis · Mathematics 2021-08-12 Yifan Chen , Bamdad Hosseini , Houman Owhadi , Andrew M Stuart

Using the theory of the symmetry group for PDEs [15, 17], we derive the symmetry group G associated to surfaces PDE. Several group invariant solutions of the surfaces PDE are given by solving a reduced system of partial differential…

Differential Geometry · Mathematics 2012-05-08 Mehdi Nadjafikhah , Parastoo Kabinejad

A diffuse interface (phase field) model for an electrochemical system is developed. We describe the minimal set of components needed to model an electrochemical interface and present a variational derivation of the governing equations. With…

Materials Science · Physics 2007-05-23 J. E. Guyer , W. J. Boettinger , J. A. Warren , G. B. McFadden

This contribution investigates the connection between isogeometric analysis and integral equation methods for full-wave electromagnetic problems up to the low-frequency limit. The proposed spline-based integral equation method allows for an…

Computational Engineering, Finance, and Science · Computer Science 2026-05-19 Maximilian Nolte , Riccardo Torchio , Sebastian Schöps , Jürgen Dölz , Felix Wolf , Albert E. Ruehli

We propose a general framework for obtaining probabilistic solutions to PDE-based inverse problems. Bayesian methods are attractive for uncertainty quantification but assume knowledge of the likelihood model or data generation process. This…

Methodology · Statistics 2023-09-28 Youngsoo Baek , Wilkins Aquino , Sayan Mukherjee

The integral-algebraic equation (IAE) is a mixed system of first-kind and second-kind Volterra integral equations (VIEs). This paper mainly focuses on the discontinuous Galerkin (DG) method to solve index-2 IAEs. First, the convergence…

Numerical Analysis · Mathematics 2024-10-10 Hecong Gao , Hui Liang

In this paper, we present a graph neural networks (GNNs)-based fast solver (GraphSolver) for solving combined field integral equations (CFIEs) of 3D conducting bodies. Rao-Wilton-Glisson (RWG) basis functions are employed to discretely and…

Machine Learning · Computer Science 2025-01-20 Tao Shan , Xin Zhang , Di Wu

Unfitted mesh formulations for interface problems generally adopt two distinct methodologies: (i) penalty-based approaches and (ii) explicit enrichment space techniques. While Stable Generalized Finite Element Method (SGFEM) has been…

Numerical Analysis · Mathematics 2025-03-21 Yin Song , Wenkai Hu , Xin Li

The generalization of neural networks is a central challenge in machine learning, especially concerning the performance under distributions that differ from training ones. Current methods, mainly based on the data-driven paradigm such as…

Machine Learning · Computer Science 2023-12-18 Yige Yuan , Bingbing Xu , Bo Lin , Liang Hou , Fei Sun , Huawei Shen , Xueqi Cheng