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This paper discusses a methodology for determining a functional representation of a random process from a collection of scattered pointwise samples. The present work specifically focuses onto random quantities lying in a high dimensional…

Numerical Analysis · Mathematics 2014-01-03 Lionel Mathelin

We derive a new discretisation method for first order PDEs of arbitrary spatial dimension, which is based upon a meshfree spatial approximation. This spatial approximation is similar to the SPH (smoothed particle hydrodynamics) technique…

Numerical Analysis · Mathematics 2016-01-25 Tobias Ramming , Holger Wendland

Covariance matrix estimation is an important problem in multivariate data analysis, both from theoretical as well as applied points of view. Many simple and popular covariance matrix estimators are known to be severely affected by model…

Methodology · Statistics 2025-11-21 Soumya Chakraborty , Ayanendranath Basu , Abhik Ghosh

We present a new meshless method for scalar diffusion equations which is motivated by their compatible discretizations on primal-dual grids. Unlike the latter though, our approach is truly meshless because it only requires the graph of…

Numerical Analysis · Mathematics 2016-10-21 Nathaniel Trask , Mauro Perego , Pavel Bochev

This paper considers the approximation of partial differential equations with a point collocation framework based on high-order local maximum-entropy schemes (HOLMES). In this approach, smooth basis functions are computed through an…

Computational Engineering, Finance, and Science · Computer Science 2020-11-02 F. Greco , M. Arroyo

When solving partial differential equations on scattered nodes using the Radial Basis Function-generated Finite Difference (RBF-FD) method, one of the parameters that must be chosen is the stencil size. Focusing on Polyharmonic Spline RBFs…

Numerical Analysis · Mathematics 2026-02-26 Andrej Kolar-Požun , Mitja Jančič , Miha Rot , Gregor Kosec

Decentralized optimization is critical for solving large-scale machine learning problems over distributed networks, where multiple nodes collaborate through local communication. In practice, the variances of stochastic gradient estimators…

Optimization and Control · Mathematics 2026-02-13 Hongxu Chen , Ke Wei , Luo Luo

Radial basis function generated finite-difference (RBF-FD) methods have recently gained popularity due to their flexibility with irregular node distributions. However, the convergence theories in the literature, when applied to nonuniform…

Numerical Analysis · Mathematics 2024-01-09 Siqing LI , Leevan Ling , Xin Liu , Pankaj K Mishra , Mrinal K Sen , Jing Zhang

We design a monotone meshfree finite difference method for linear elliptic equations in the non-divergence form on point clouds via a nonlocal relaxation method. The key idea is a novel combination of a nonlocal integral relaxation of the…

Numerical Analysis · Mathematics 2023-08-08 Qihao Ye , Xiaochuan Tian

Mesh-free numerical methods provide flexible discretisations for complex geometries; however, classical meshless discrete differential operators typically trade low computational cost for limited accuracy or high accuracy for substantial…

Machine Learning · Computer Science 2026-03-27 Lucas Gerken Starepravo , Georgios Fourtakas , Steven Lind , Ajay B. Harish , Tianning Tang , Jack R. C. King

Accurate modeling of complex physical problems, such as fluid-structure interaction, requires multiphysics coupling across the interface, which often has intricate geometry and dynamic boundaries. Conventional numerical methods face…

Numerical Analysis · Mathematics 2023-08-08 Yunlong Li , Fei Wang

We introduce an adaptive scattered data fitting scheme as extension of local least squares approximations to hierarchical spline spaces. To efficiently deal with non-trivial data configurations, the local solutions are described in terms of…

Numerical Analysis · Mathematics 2017-04-28 Cesare Bracco , Carlotta Giannelli , Alessandra Sestini

Approximation/interpolation from spaces of positive definite or conditionally positive definite kernels is an increasingly popular tool for the analysis and synthesis of scattered data, and is central to many meshless methods. For a set of…

Numerical Analysis · Mathematics 2013-09-11 E. Fuselier , T. Hangelbroek , F. J. Narcowich , J. D. Ward , G. B. Wright

This paper presents a rigorous numerical framework for computing multiple solutions of semilinear elliptic problems by spatiotemporal high-index saddle dynamics (HiSD), which extends the traditional HiSD to the continuous-in-space setting,…

Numerical Analysis · Mathematics 2026-01-14 Lei Zhang , Xiangcheng Zheng , Shangqin Zhu

In order to avoid the curse of dimensionality, frequently encountered in Big Data analysis, there was a vast development in the field of linear and nonlinear dimension reduction techniques in recent years. These techniques (sometimes…

Graphics · Computer Science 2020-02-27 Barak Sober , David Levin

The popularity of local meshless methods in the field of numerical simulations has increased greatly in recent years. This is mainly due to the fact that they can operate on scattered nodes and that they allow a direct control over the…

Numerical Analysis · Mathematics 2022-06-29 Mitja Jančič , Gregor Kosec

Particle-based methods are a practical tool in computational fluid dynamics, and novel types of methods have been proposed. However, widely developed Lagrangian-type formulations suffer from the nonuniform distribution of particles, which…

Fluid Dynamics · Physics 2025-03-26 Takeharu Matsuda , Satoshi Ii

A parallel implementation of a compatible discretization scheme for steady-state Stokes problems is presented in this work. The scheme uses generalized moving least squares to generate differential operators and apply boundary conditions.…

Numerical Analysis · Mathematics 2021-04-30 Quang-Thinh Ha , Paul A. Kuberry , Nathaniel A. Trask , Emily M. Ryan

We develop a new spatial semidiscrete multiscale method based upon the edge multiscale methods to solve semilinear parabolic problems with heterogeneous coefficients and smooth initial data. This method allows for a cheap spatial…

Numerical Analysis · Mathematics 2025-12-16 Leonardo A. Poveda , Shubin Fu , Guanglian Li , Eric Chung

This paper introduces a novel meshfree methodology based on Radial Basis Function-Finite Difference (RBF-FD) approximations for the numerical solution of partial differential equations (PDEs) on surfaces of codimension 1 embedded in…

Numerical Analysis · Mathematics 2024-12-20 Víctor Bayona , Argyrios Petras , Cécile Piret , Steven J. Ruuth