We give a new fast method for evaluating sprectral approximations of nonlinear polynomial functionals. We prove that the new algorithm is convergent if the functions considered are smooth enough, under a general assumption on the spectral eigenfunctions that turns out to be satisfied in many cases, including the Fourier and Hermite basis
AbstractWe propose the construction of a mixing filter for the detection of analytic singularities a...
We consider the problem of Lagrange polynomial interpolation in high or countably infinite dimension...
Abstract. Polynomial approximations of computationally intensive models are central to uncertainty q...
We give a new fast method for evaluating sprectral approximations of nonlinear polynomial functional...
We give a new fast method for evaluating sprectral approximations of nonlinear polynomial functional...
We give a new fast method for evaluating sprectral approximations of non-linear polynomial functiona...
Multivariate global polynomial approximations – such as polynomial chaos or stochastic collocation m...
Multivariate global polynomial approximations – such as polynomial chaos or stochastic collocation m...
Sparse polynomial approximation has become indispensable for approximating smooth, high- or infinite...
AbstractIn this paper modified variants of the sparse Fourier transform algorithms from Iwen (2010) ...
In this thesis we analyse the approximation of countably-parametric functions $u$ and their expectat...
Multivariate global polynomial approximations – such as polynomial chaos or stochastic collocation m...
In this paper, we demonstrate that many of the computational tools for univariate orthogonal polynom...
AbstractIn Part I we introduced the generalized Wiener rational basis functions, and here in Part II...
We construct a sequence of globally defined polynomial valued operators, using linear combinations o...
AbstractWe propose the construction of a mixing filter for the detection of analytic singularities a...
We consider the problem of Lagrange polynomial interpolation in high or countably infinite dimension...
Abstract. Polynomial approximations of computationally intensive models are central to uncertainty q...
We give a new fast method for evaluating sprectral approximations of nonlinear polynomial functional...
We give a new fast method for evaluating sprectral approximations of nonlinear polynomial functional...
We give a new fast method for evaluating sprectral approximations of non-linear polynomial functiona...
Multivariate global polynomial approximations – such as polynomial chaos or stochastic collocation m...
Multivariate global polynomial approximations – such as polynomial chaos or stochastic collocation m...
Sparse polynomial approximation has become indispensable for approximating smooth, high- or infinite...
AbstractIn this paper modified variants of the sparse Fourier transform algorithms from Iwen (2010) ...
In this thesis we analyse the approximation of countably-parametric functions $u$ and their expectat...
Multivariate global polynomial approximations – such as polynomial chaos or stochastic collocation m...
In this paper, we demonstrate that many of the computational tools for univariate orthogonal polynom...
AbstractIn Part I we introduced the generalized Wiener rational basis functions, and here in Part II...
We construct a sequence of globally defined polynomial valued operators, using linear combinations o...
AbstractWe propose the construction of a mixing filter for the detection of analytic singularities a...
We consider the problem of Lagrange polynomial interpolation in high or countably infinite dimension...
Abstract. Polynomial approximations of computationally intensive models are central to uncertainty q...