A traditional criterion to calculate the numerical stability of the interpolation matrix is its
standard condition number. In this paper, it is observed that the effective condition number (κ …

In this work we develop the standard Hermite interpolation based RBF-generated finite
difference (RBF-HFD) method into a new faster and more accurate technique based on …

Thanks to their easy implementation via radial basis functions (RBFs), meshfree kernel
methods have proved to be an effective tool for, eg, scattered data interpolation, PDE …

This paper explores the utilization of randomized SVD (rSVD) in the context of kernel
matrices arising from radial basis functions (RBFs) for the purpose of solving interpolation …

We construct cubature methods on scattered data via resampling on the support of known
algebraic cubature formulas, by different kinds of adaptive interpolation (polynomial, RBF …

In this paper we present a new fast and accurate method for Radial Basis Function (RBF)
approximation, including interpolation as a special case, which enables us to effectively find …

In this article we propose an adaptive algorithm for the solution of time-dependent boundary
value problems (BVPs). To solve numerically these problems, we consider the kernel-based …

The target of this research is to resolve high-dimensional partial differential equations
(PDEs) for multi-asset options, modeled as parabolic time-dependent PDEs. We present a …

In this paper, we employ Bayesian optimization to concurrently explore the optimal values
for both the shape parameter and the radius in the partition of unity interpolation using radial …

Radial basis functions (RBFs) play an important role in function interpolation, in particular in
an arbitrary set of interpolation nodes. The accuracy of the interpolation depends on a …