English
Related papers

Related papers: An embedded method-of-lines approach to solving pa…

200 papers

We apply polynomial approximation methods -- known in the numerical PDEs context as spectral methods -- to approximate the vector-valued function that satisfies a linear system of equations where the matrix and the right hand side depend on…

Numerical Analysis · Mathematics 2013-05-21 Paul G. Constantine , David F. Gleich , Gianluca Iaccarino

We develop a geometrically intrinsic formulation of the arbitrary-order Virtual Element Method (VEM) on polygonal cells for the numerical solution of elliptic surface partial differential equations (PDEs). The PDE is first written in…

Numerical Analysis · Mathematics 2021-05-07 Elena Bachini , Gianmarco Manzini , Mario Putti

Embeddings provide low-dimensional representations that organize complex function spaces and support generalization. They provide a geometric representation that supports efficient retrieval, comparison, and generalization. In this work we…

Analysis of PDEs · Mathematics 2026-03-10 Pedro Tarancón-Álvarez , Leonid Sarieddine , Pavlos Protopapas , Raul Jimenez

In this paper, we proposed two new types of edge multiscale methods motivated by \cite{GL18} to solve Partial Differential Equations (PDEs) with high-contrast heterogeneous coefficients: Edge spectral multiscale Finte Element method…

Numerical Analysis · Mathematics 2019-09-04 Shubin Fu , Eric Chung , Guanglian Li

We present a continuous/discontinuous Galerkin method for approximating solutions to a fourth order elliptic PDE on a surface embedded in $\mathbb{R}^3$. A priori error estimates, taking both the approximation of the surface and the…

Numerical Analysis · Mathematics 2017-06-23 Karl Larsson , Mats G. Larson

We apply the semi-discrete method, c.f. \emph{N. Halidias and I.S. Stamatiou (2016), On the numerical solution of some non-linear stochastic differential equations using the semi-discrete method, Computational Methods in Applied…

Numerical Analysis · Mathematics 2018-07-25 Ioannis S. Stamatiou

The branching methods developed are effective methods to solve some semi linear PDEs and are shown numerically to be able to solve some full non linear PDEs. These methods are however restricted to some small coefficients in the PDE and…

Probability · Mathematics 2017-01-27 Xavier Warin

Consider the problem of minimizing the sum of two convex functions, one being smooth and the other non-smooth. In this paper, we introduce a general class of approximate proximal splitting (APS) methods for solving such minimization…

Optimization and Control · Mathematics 2014-04-23 Mojtaba Kadkhodaie , Maziar Sanjabi , Zhi-Quan Luo

Edge-preserving smoothing (EPS) can be formulated as minimizing an objective function that consists of data and prior terms. This global EPS approach shows better smoothing performance than a local one that typically has a form of weighted…

Computer Vision and Pattern Recognition · Computer Science 2016-04-27 Youngjung Kim , Dongbo Min , Bumsub Ham , Kwanghoon Sohn

In this paper, a physics-informed multiresolution wavelet neural network (PIMWNN) method is proposed for solving partial differential equations (PDEs). This method uses the multiresolution wavelet neural network (MWNN) to approximate…

Numerical Analysis · Mathematics 2025-08-12 Feng Han , Jianguo Wang , Guoliang Peng , Xueting Shi

In this paper we present a new Eulerian finite element method for the discretization of scalar partial differential equations on evolving surfaces. In this method we use the restriction of standard space-time finite element spaces on a…

Numerical Analysis · Mathematics 2022-12-26 Hauke Sass , Arnold Reusken

We introduce suitable coordinate systems for pipes and their variants that allow us to transform partial differential equations (PDEs) on the pipe surfaces or in the solid pipes into computational domains with fixed limits/ranges. Such a…

Numerical Analysis · Mathematics 2025-09-09 Shuaifei Hu , Yujian Jiao , Desong Kong , Li-Lian Wang

In recent years, deep learning technology has been used to solve partial differential equations (PDEs), among which the physics-informed neural networks (PINNs) emerges to be a promising method for solving both forward and inverse PDE…

Machine Learning · Computer Science 2021-11-03 Xiang Huang , Hongsheng Liu , Beiji Shi , Zidong Wang , Kang Yang , Yang Li , Bingya Weng , Min Wang , Haotian Chu , Jing Zhou , Fan Yu , Bei Hua , Lei Chen , Bin Dong

A numerical method for coupled 3D-1D problems with discontinuous solutions at the interfaces is derived and discussed. This extends a previous work on the subject where only continuous solutions were considered. Thanks to properly defined…

Numerical Analysis · Mathematics 2022-03-04 Stefano Berrone , Denise Grappein , Stefano Scialò

Partial differential equations (PDE) on manifolds arise in many areas, including mathematics and many applied fields. Among all kinds of PDEs, the Poisson-type equations including the standard Poisson equation and the related eigenproblem…

Numerical Analysis · Mathematics 2015-08-05 Zhen Li , Zuoqiang Shi , Jian Sun

This article aims to develop a direct numerical approach to solve the space-fractional partial differential equations (PDEs) based on a new differential quadrature (DQ) technique. The fractional derivatives are approximated by the weighted…

Numerical Analysis · Mathematics 2017-01-24 X. G. Zhu , Y. F. Nie

The study gives a brief overview of existing modifications of the method of functional separation of variables for nonlinear PDEs. It proposes a more general approach to the construction of exact solutions to nonlinear equations of applied…

Mathematical Physics · Physics 2020-01-07 Andrei D. Polyanin

We present a method to simulate fluid flow on evolving surfaces, e.g., an oil film on a water surface. Given an animated surface (e.g., extracted from a particle-based fluid simulation) in three-dimensional space, we add a second simulation…

Graphics · Computer Science 2020-10-08 Dieter Morgenroth , Stefan Reinhardt , Daniel Weiskopf , Bernhard Eberhardt

The multiscale complexity of modern problems in computational science and engineering can prohibit the use of traditional numerical methods in multi-dimensional simulations. Therefore, novel algorithms are required in these situations to…

Numerical Analysis · Mathematics 2021-06-15 Cale Harnish , Luke Dalessandro , Karel Matous , Daniel Livescu

We present a reduced basis (RB) method for parametrized linear elliptic partial differential equations (PDEs) in a least-squares finite element framework. A rigorous and reliable error estimate is developed, and is shown to bound the error…

Numerical Analysis · Mathematics 2020-09-24 Jehanzeb Hameed Chaudhry , Luke N. Olson , Peter Sentz