General elliptic equations with spatially discontinuous diffusion coefficients may be used as a simplified model for subsurface flow in heterogeneous or fractured porous media. In such a model, data sparsity and measurement errors are often taken into account by a randomization of the diffusion coefficient of the elliptic equation which reveals the necessity of the construction of flexible, spatially discontinuous random fields. Subordinated Gaussian random fields are random functions on higher dimensional parameter domains with discontinuous sample paths and great distributional flexibility. In the present work, we consider a random elliptic partial differential equation (PDE) where the discontinuous subordinated Gaussian random fields occ...
We consider the numerical approximation of the stochastic Darcy problem with log-normal permeability...
As an extension to the well-established stationary elliptic partial differential equation (PDE) with...
We devise and implement quasi-Monte Carlo methods for computing the expectations of nonlinear functi...
We consider the numerical approximation of a partial differential equation (PDE) with random co-effi...
We consider Gaussian subordinated L\'evy fields (GSLFs) that arise by subordinating L\'evy processes...
We present a Multi-Index Quasi-Monte Carlo method for the solution of elliptic partial differential ...
In Monte Carlo methods quadrupling the sample size halves the error. In simulations of stochastic pa...
The aim of this paper is to show that a high-order discretization can be used to improve the converg...
We consider the numerical solution of elliptic partial differential equations with random coefficien...
Abstract We consider the numerical solution of elliptic par-tial differential equations with random ...
We analyze the recent Multi-index Stochastic Collocation (MISC) method for computing statistics of t...
We consider elliptic diffusion problems with a random anisotropic diffusion coefficient, where, in a...
We consider the application of multilevel Monte Carlo methods to elliptic PDEs with ran-dom coeffici...
We present a Multilevel Quasi-Monte Carlo algorithm for the solution of elliptic partial differentia...
Multilevel Monte Carlo finite element methods (MLMC-FEMs) for the solution of stochastic elliptic va...
We consider the numerical approximation of the stochastic Darcy problem with log-normal permeability...
As an extension to the well-established stationary elliptic partial differential equation (PDE) with...
We devise and implement quasi-Monte Carlo methods for computing the expectations of nonlinear functi...
We consider the numerical approximation of a partial differential equation (PDE) with random co-effi...
We consider Gaussian subordinated L\'evy fields (GSLFs) that arise by subordinating L\'evy processes...
We present a Multi-Index Quasi-Monte Carlo method for the solution of elliptic partial differential ...
In Monte Carlo methods quadrupling the sample size halves the error. In simulations of stochastic pa...
The aim of this paper is to show that a high-order discretization can be used to improve the converg...
We consider the numerical solution of elliptic partial differential equations with random coefficien...
Abstract We consider the numerical solution of elliptic par-tial differential equations with random ...
We analyze the recent Multi-index Stochastic Collocation (MISC) method for computing statistics of t...
We consider elliptic diffusion problems with a random anisotropic diffusion coefficient, where, in a...
We consider the application of multilevel Monte Carlo methods to elliptic PDEs with ran-dom coeffici...
We present a Multilevel Quasi-Monte Carlo algorithm for the solution of elliptic partial differentia...
Multilevel Monte Carlo finite element methods (MLMC-FEMs) for the solution of stochastic elliptic va...
We consider the numerical approximation of the stochastic Darcy problem with log-normal permeability...
As an extension to the well-established stationary elliptic partial differential equation (PDE) with...
We devise and implement quasi-Monte Carlo methods for computing the expectations of nonlinear functi...