72 citations · 536 across the 51 of their papers we have counts for
5 papers · 1 filter
To be or not to be intrusive? The solution of parametric and stochastic equations - the "plain vanilla" Galerkin case
Loïc Giraldi, Alexander Litvinenko, Dishi Liu +2
In parametric equations - stochastic equations are a special case - one may want to approximate the solution such that it is easy to evaluate its dependence of the parameters. Inte…
A least-squares method for sparse low rank approximation of multivariate functions
Mathilde Chevreuil, Régis Lebrun, Anthony Nouy +1
In this paper, we propose a low-rank approximation method based on discrete least-squares for the approximation of a multivariate function from random, noisy-free observations. Spa…
Low-rank approximate inverse for preconditioning tensor-structured linear systems
Loic Giraldi, Anthony Nouy, Gregory Legrain
In this paper, we propose an algorithm for the construction of low-rank approximations of the inverse of an operator given in low-rank tensor format. The construction relies on an…
A tensor approximation method based on ideal minimal residual formulations for the solution of high-dimensional problems
Marie Billaud-Friess, Anthony Nouy, Olivier Zahm
In this paper, we propose a method for the approximation of the solution of high-dimensional weakly coercive problems formulated in tensor spaces using low-rank approximation forma…
Random fields representations for stochastic elliptic boundary value problems and statistical inverse problems
Anthony Nouy, Christian Soize
This paper presents new results allowing an unknown non-Gaussian positive matrix-valued random field to be identified through a stochastic elliptic boundary value problem, solving…