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We introduce and investigate matrix approximation by decomposition into a sum of radial basis function (RBF) components. An RBF component is a generalization of the outer product between a pair of vectors, where an RBF function replaces the…

Machine Learning · Computer Science 2021-06-25 Elizaveta Rebrova , Yu-Hang Tang

This paper proposes a Direct Rational Radial Basis Functions Partition of Unity (D-RRBF-PU) approach to compute derivatives of functions with steep gradients or discontinuities. The novelty of the method concerns how derivatives are…

Numerical Analysis · Mathematics 2025-01-13 Vahid Mohammadi , Stefano De Marchi

We develop efficient and high-order accurate finite difference methods for elliptic partial differential equations in complex geometry in the Difference Potentials framework. The main novelty of the developed schemes is the use of local…

Numerical Analysis · Mathematics 2023-06-28 Qing Xia

We present a computational scheme that derives a global polynomial level set parametrisation for smooth closed surfaces from a regular surface-point set and prove its uniqueness. This enables us to approximate a broad class of smooth…

Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for large scattered (unordered) datasets in d-dimensional space. This approach is useful for a higher…

Numerical Analysis · Computer Science 2018-06-21 Zuzana Majdisova , Vaclav Skala

This paper proposes a novel Generalized Non-Standard Finite Difference (GNSFD) scheme for the numerical solution of a class of fractional partial differential equations (FrPDEs). The formulation of the method is grounded in optimization and…

Numerical Analysis · Mathematics 2025-09-17 Devank Mishra , Sheerin Kayenat , Amit K. Verma

Very few studies involve how to construct the efficient RBFs by means of problem features. Recently the present author presented general solution RBF (GS-RBF) methodology to create operator-dependent RBFs successfully [1]. On the other…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 W. Chen

Finite volume methods (FVMs) constitute a popular class of methods for the numerical simulation of fluid flows. Among the various components of these methods, the discretisation of the gradient operator has received less attention despite…

Numerical Analysis · Computer Science 2018-01-03 Alexandros Syrakos , Stylianos Varchanis , Yannis Dimakopoulos , Apostolos Goulas , John Tsamopoulos

We develop numerical methods for computing statistics of stochastic processes on surfaces of general shape with drift-diffusion dynamics $d\mathbf{X}_t = a(\mathbf{X}_t)dt + \mathbf{b}(\mathbf{X}_t)d\mathbf{W}_t$. We formulate descriptions…

Numerical Analysis · Mathematics 2023-02-28 B. J. Gross , P. Kuberry , P. J. Atzberger

We present adaptive finite difference ENO/WENO methods by adopting infinitely smooth radial basis functions (RBFs). This is a direct extension of the non-polynomial finite volume ENO/WENO method proposed by authors in \cite{GuoJung} to the…

Numerical Analysis · Mathematics 2017-05-23 Jingyang Guo , Jae-Hun Jung

A new discretisation scheme for the gradient operator, suitable for use in second-order accurate Finite Volume Methods (FVMs), is proposed. The derivation of this scheme, which we call the Taylor-Gauss (TG) gradient, is similar to that of…

Rapid and accurate simulations of fluid dynamics around complicated geometric bodies are critical in a variety of engineering and scientific applications, including aerodynamics and biomedical flows. However, while scientific machine…

In this paper, we analyze several methods for approximating gradients of noisy functions using only function values. These methods include finite differences, linear interpolation, Gaussian smoothing and smoothing on a sphere. The methods…

Optimization and Control · Mathematics 2021-03-29 Albert S. Berahas , Liyuan Cao , Krzysztof Choromanski , Katya Scheinberg

Derivative-free optimization (DFO) is vital in solving complex optimization problems where only noisy function evaluations are available through an oracle. Within this domain, DFO via finite difference (FD) approximation has emerged as a…

Machine Learning · Computer Science 2025-02-19 Wang Du-Yi , Liang Guo , Liu Guangwu , Zhang Kun

Consider an $s$-dimensional function being evaluated at $n$ points of a low discrepancy sequence (LDS), where the objective is to approximate the one-dimensional functions that result from integrating out $(s-1)$ variables. Here, the…

Numerical Analysis · Mathematics 2019-11-11 Chaitanya Joshi , Paul T. Brown , Stephen Joe

Radial basis function generated finite difference (RBF-FD) methods for PDEs require a set of interpolation points which conform to the computational domain $\Omega$. One of the requirements leading to approximation robustness is to place…

Numerical Analysis · Mathematics 2021-04-07 Igor Tominec , Eva Breznik

Mesh-free methods have significant potential for simulations in complex geometries, as the time consuming process of mesh-generation is avoided. Smoothed Particle Hydrodynamics (SPH) is the most widely used mesh-free method, but suffers…

Computational Physics · Physics 2020-06-24 Jack King , Steven Lind , Abouzied Nasar

We present a high-order radial basis function finite difference (RBF-FD) framework for the solution of advection-diffusion equations on time-varying domains. Our framework is based on a generalization of the recently developed Overlapped…

Numerical Analysis · Mathematics 2021-09-15 Varun Shankar , Grady B. Wright , Aaron L. Fogelson

Because of the nonlocal properties of fractional operators, higher order schemes play more important role in discretizing fractional derivatives than classical ones. The striking feature is that higher order schemes of fractional…

Numerical Analysis · Mathematics 2014-06-17 Minghua Chen , Weihua Deng

We present three new semi-Lagrangian methods based on radial basis function (RBF) interpolation for numerically simulating transport on a sphere. The methods are mesh-free and are formulated entirely in Cartesian coordinates, thus avoiding…

Numerical Analysis · Mathematics 2018-05-09 Varun Shankar , Grady Wright
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