The discretization of linear partial differential equations with random data by means of the
stochastic Galerkin finite element method results in general in a large coupled linear system …

Use of the stochastic Galerkin finite element methods leads to large systems of linear
equations obtained by the discretization of tensor product solution spaces along their spatial …

We introduce a stochastic Galerkin mixed formulation of the steady-state diffusion equation
and focus on the efficient iterative solution of the saddle-point systems obtained by …

We consider the numerical solution of a steady-state diffusion problem where the diffusion
coefficient is the exponent of a random field. The standard stochastic Galerkin formulation of …

We study the solution of linear systems resulting from the discretization of unsteady diffusion
equations with stochastic coefficients. In particular, we focus on those linear systems that are …

In the last five years, the scientific computing community has taken great interest in the so-
called stochastic Galerkin schemes (SGS). These schemes are typically used to address the …

Stochastic Galerkin finite element discretizations of partial differential equations with
coefficients characterized by arbitrary distributions lead, in general, to fully block dense …

In this paper we propose and analyze a stochastic collocation method to solve elliptic partial
differential equations with random coefficients and forcing terms (input data of the model) …

This paper presents an overview and comparison of iterative solvers for linear stochastic
partial differential equations (PDEs). A stochastic Galerkin finite element discretization is …

We describe and analyze two numerical methods for a linear elliptic problem with stochastic
coefficients and homogeneous Dirichlet boundary conditions. Here the aim of the …