Abstract. This paper proves convergence of variations of the unsymmetric kernel-based collocation method introduced by E. Kansa in 1986. Since then, this method has been very successfully used in many applications, though it may theoretically fail in special situations, and though it had no error bound or convergence proof up to now. Thus it is necessary to add assumptions or to make modifications. Our modifications will prevent numerical failure and allow a rigorous mathematical analysis proving error bounds and convergence rates. These rates improve with the smoothness of the solution, the domain, and the kernel providing the trial spaces, but they are currently not yet optimal and deserve refinement. They are based on rates of approximat...
We present a meshless technique which can be seen as an alternative to the Method of Fundamental Sol...
We present greedy unsymmetric collocation schemes for solving linear elliptic partial differential e...
International audienceA conservative linear surface approximation (CLS) has been recently introduced...
In the past two decades substantial advancements of meshfree methods have been made for various engi...
This is a short summary of recent mathematical results on error bounds and convergence of certain un...
Meshless method can be mainly divided into, according its discretizing principle, two kinds of type:...
Introduction We will treat systems of linear equations, each of the form Lu = f on\Omega ; (1.1)...
Kernel based methods provide a way to reconstruct potentially high-dimensional functions from meshfr...
Meshless collocation methods for the numerical solution of partial differen-tial equations have rece...
In this paper, we derive error estimates for generalized interpolation, in particular collocation, i...
summary:Mesh-independent convergence of Newton-type methods for the solution of nonlinear partial di...
In this paper, we study the stability of symmetric collocation methods for boundary value problems u...
Error estimates for kernel interpolation in Reproducing Kernel Hilbert Spaces (RKHS) usually assume ...
In Machine Learning algorithms, one of the crucial issues is the representation of the data. As the ...
peer reviewedA novel space-time meshfree collocation method (STMCM) for solving systems of non-linea...
We present a meshless technique which can be seen as an alternative to the Method of Fundamental Sol...
We present greedy unsymmetric collocation schemes for solving linear elliptic partial differential e...
International audienceA conservative linear surface approximation (CLS) has been recently introduced...
In the past two decades substantial advancements of meshfree methods have been made for various engi...
This is a short summary of recent mathematical results on error bounds and convergence of certain un...
Meshless method can be mainly divided into, according its discretizing principle, two kinds of type:...
Introduction We will treat systems of linear equations, each of the form Lu = f on\Omega ; (1.1)...
Kernel based methods provide a way to reconstruct potentially high-dimensional functions from meshfr...
Meshless collocation methods for the numerical solution of partial differen-tial equations have rece...
In this paper, we derive error estimates for generalized interpolation, in particular collocation, i...
summary:Mesh-independent convergence of Newton-type methods for the solution of nonlinear partial di...
In this paper, we study the stability of symmetric collocation methods for boundary value problems u...
Error estimates for kernel interpolation in Reproducing Kernel Hilbert Spaces (RKHS) usually assume ...
In Machine Learning algorithms, one of the crucial issues is the representation of the data. As the ...
peer reviewedA novel space-time meshfree collocation method (STMCM) for solving systems of non-linea...
We present a meshless technique which can be seen as an alternative to the Method of Fundamental Sol...
We present greedy unsymmetric collocation schemes for solving linear elliptic partial differential e...
International audienceA conservative linear surface approximation (CLS) has been recently introduced...