Add to ORKGWe present an algorithm to approximate large dataset by Radial Basis Function (RBF) techniques. The method couples a fast domain decomposition procedure with a localized stabilization method. The resulting algorithm can efficiently deal with large problems and it is robust with respect to the typical instability of kernel methods
In this paper we propose two fast localized radial basis function fitting algorithms for solving lar...
We present here a new stable algorithm for the small ϵ (flat basis function) limit in Radial Basis Fu...
AbstractTo better approximate nearly singular functions with meshless methods, we propose a data poi...
This paper is dedicated to Prof. Francesco A. Costabile on the occasion of his 70th birthday In this...
In this paper we propose a new stable and accurate approximation technique which is extremely effect...
In this paper we propose a new stable and accurate approximation technique which is extremely effect...
3We perform a local computation via the Partition of Unity (PU) method of rational Radial Basis Func...
We perform a local computation via the Partition of Unity (PU) method of rational Radial Basis Funct...
We perform a local computation via the Partition of Unity (PU) method of rational Radial Basis Funct...
One commonly finds in applications of smooth radial basis functions (RBFs) that scaling the kernels ...
We present a new scheme for the reconstruction of large geometric data. It is based on the well-know...
We combine the theory of radial basis function interpolation with a partition of unity method to so...
4noWe investigate adaptivity issues for the approximation of Poisson equations via radial basis fun...
The computation of global radial basis function (RBF) approximations requires the solution of a line...
Most traditional numerical methods for approximating the solutions of problems in science, engineeri...
In this paper we propose two fast localized radial basis function fitting algorithms for solving lar...
We present here a new stable algorithm for the small ϵ (flat basis function) limit in Radial Basis Fu...
AbstractTo better approximate nearly singular functions with meshless methods, we propose a data poi...
This paper is dedicated to Prof. Francesco A. Costabile on the occasion of his 70th birthday In this...
In this paper we propose a new stable and accurate approximation technique which is extremely effect...
In this paper we propose a new stable and accurate approximation technique which is extremely effect...
3We perform a local computation via the Partition of Unity (PU) method of rational Radial Basis Func...
We perform a local computation via the Partition of Unity (PU) method of rational Radial Basis Funct...
We perform a local computation via the Partition of Unity (PU) method of rational Radial Basis Funct...
One commonly finds in applications of smooth radial basis functions (RBFs) that scaling the kernels ...
We present a new scheme for the reconstruction of large geometric data. It is based on the well-know...
We combine the theory of radial basis function interpolation with a partition of unity method to so...
4noWe investigate adaptivity issues for the approximation of Poisson equations via radial basis fun...
The computation of global radial basis function (RBF) approximations requires the solution of a line...
Most traditional numerical methods for approximating the solutions of problems in science, engineeri...
In this paper we propose two fast localized radial basis function fitting algorithms for solving lar...
We present here a new stable algorithm for the small ϵ (flat basis function) limit in Radial Basis Fu...
AbstractTo better approximate nearly singular functions with meshless methods, we propose a data poi...