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Material properties such as permeability fields in heterogeneous porous media are often represented as discontinuous, piecewise constant data tied to a given spatial discretization. Such representations are inherently mesh-dependent,…

Numerical Analysis · Mathematics 2026-05-19 Kapil Chawla , Sanghyun Lee , Yeonjong Shin

In this note we shall introduce a simple, effective numerical method for solving partial differential equations for scalar and vector-valued data defined on surfaces. Even though we shall follow the traditional way to approximate the…

Computational Geometry · Computer Science 2009-07-13 Sheng-Gwo Chen , Mei-Hsiu Chi , Jyh-Yang Wu

In this work, we develop a high-order collocation method using radial basis function (RBF) for the incompressible Navier-Stokes equation (NSE) on the rotating sphere. The method is based on solving the projection of the NSE on the space of…

Numerical Analysis · Mathematics 2022-04-27 Tino Franz

We introduce a Trajectory-Based RBF Collocation (TBRBF) method for solving surface advection-diffusion equations on smooth, compact manifolds. TBRBF decouples advection and diffusion by applying a characteristic treatment with a Kansa-type…

Numerical Analysis · Mathematics 2026-01-27 Xiaobin Li , Leevan Ling , Yizhong Sun

The random feature method (RFM) has demonstrated great potential in bridging traditional numerical methods and machine learning techniques for solving partial differential equations (PDEs). It retains the advantages of mesh-free approaches…

Numerical Analysis · Mathematics 2025-05-02 Mikhail Kuvakin , Zijian Mei , Jingrun Chen

Partial differential equations (PDEs) with near singular solutions pose significant challenges for traditional numerical methods, particularly in complex geometries where mesh generation and adaptive refinement become computationally…

Numerical Analysis · Mathematics 2025-07-24 Yangtao Deng , Qiaolin He , Xiaoping Wang

Local meshless methods using RBFs augmented with monomials have become increasingly popular, due to the fact that they can be used to solve PDEs on scattered node sets in a dimension-independent way, with the ability to easily control the…

Numerical Analysis · Mathematics 2022-01-28 Mitja Jančič , Jure Slak , Gregor Kosec

We present a non-nested multilevel algorithm for solving the Poisson equation discretized at scattered points using polyharmonic radial basis function (PHS-RBF) interpolations. We append polynomials to the radial basis functions to achieve…

Numerical Analysis · Mathematics 2021-04-29 Anand Radhakrishnan , Michael Xu , Shantanu Shahane , Surya Pratap Vanka

We develop a new meshfree geometric multilevel (MGM) method for solving linear systems that arise from discretizing elliptic PDEs on surfaces represented by point clouds. The method uses a Poisson disk sampling-type technique for coarsening…

Numerical Analysis · Mathematics 2022-04-14 Grady B. Wright , Andrew M. Jones , Varun Shankar

Recovered finite element methods (R-FEM) have been recently introduced for meshes consisting of simplicial and/or box-type meshes. Here, utilising the flexibility of R-FEM framework, we extend their definition on polygonal and polyhedral…

Numerical Analysis · Mathematics 2018-04-24 Zhaonan Dong , Emmanuil H. Georgoulis , Tristan Pryer

Diffusion probabilistic models (DPMs) are widely adopted for their outstanding generative fidelity, yet their sampling is computationally demanding. Polynomial-based multistep samplers mitigate this cost by accelerating inference; however,…

Machine Learning · Computer Science 2026-03-17 Soochul Park , Yeon Ju Lee , SeongJin Yoon , Jiyub Shin , Juhee Lee , Seongwoon Jo

The paper develops a finite element method for partial differential equations posed on hypersurfaces in $\mathbb{R}^N$, $N=2,3$. The method uses traces of bulk finite element functions on a surface embedded in a volumetric domain. The bulk…

Numerical Analysis · Mathematics 2023-07-19 Alexey Y. Chernyshenko , Maxim A. Olshanskii

We present a rigorous convergence analysis for cylindrical approximations of nonlinear functionals, functional derivatives, and functional differential equations (FDEs). The purpose of this analysis is twofold: first, we prove that…

Numerical Analysis · Mathematics 2021-03-17 Daniele Venturi , Alec Dektor

Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for large scattered datasets in d-dimensional space. It is non-separable approximation, as it is…

Numerical Analysis · Mathematics 2018-06-13 Zuzana Majdisova , Vaclav Skala

This work addresses a novel version of the kernel-free boundary integral (KFBI) method for solving elliptic PDEs with implicitly defined irregular boundaries and interfaces. We focus on boundary value problems and interface problems, which…

Numerical Analysis · Mathematics 2023-09-13 Han Zhou , Wenjun Ying

Scattered data interpolation schemes using kriging and radial basis functions (RBFs) have the advantage of being meshless and dimensional independent, however, for the data sets having insufficient observations, RBFs have the advantage over…

Numerical Analysis · Mathematics 2018-06-12 Pankaj K Mishra , Sankar K Nath , Mrinal K Sen , Gregory E Fasshauer

We present a spectrally accurate embedded boundary method for solving linear, inhomogeneous, elliptic partial differential equations (PDE) in general smooth geometries, focusing in this manuscript on the Poisson, modified Helmholtz, and…

Numerical Analysis · Mathematics 2022-09-28 David B. Stein

This paper investigates the existence of localised axisymmetric (radial) patterns on the surface of a ferrofluid in the presence of a uniform vertical magnetic field. We formally investigate all possible small-amplitude solutions which…

Dynamical Systems · Mathematics 2022-03-18 Dan J. Hill , David J. B. Lloyd , Matthew R. Turner

A new field of numerical astrophysics is introduced which addresses the solution of large, multidimensional structural or slowly-evolving problems (rotating stars, interacting binaries, thick advective accretion disks, four dimensional…

Astrophysics · Physics 2009-10-30 David L. Meier

We propose an approach to solving partial differential equations (PDEs) using a set of neural networks which we call Neural Basis Functions (NBF). This NBF framework is a novel variation of the POD DeepONet operator learning approach where…

Machine Learning · Computer Science 2022-08-04 David Witman , Alexander New , Hicham Alkendry , Honest Mrema