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A posteriori error estimation for partial differential equations with random input data

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Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients

Fabio Nobile, Lorenzo Tamellini

In this work we consider quasi-optimal versions of the Stochastic Galerkin method for solving linear elliptic PDEs with stochastic coefficients. In particular, we consider the case of a finite number

N

of random inputs and an analytic dependence of the s ...

2014

A posteriori error estimation for partial differential equations with random input data

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Chattez avec Graph Search

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Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients

MATHICSE Technical Report : Reduced basis approximation and a posteriori error estimates for parametrized elliptic eigenvalue problems

Error Analysis of the Dynamically Orthogonal Approximation of Time Dependent Random PDEs

Lyapunov exponents of random walks in small random potential: the upper bound

MATHICSE Technical Report : A continuation multilevel Monte Carlo algorithm

MATHICSE Technical Report : On the dynamically orthogonal approximation of time dependent random PDEs

MATHICSE Technical Report : A posteriori error estimations for elliptic partial differential equations with small uncertainties

MATHICSE Technical Report : Optimization of mesh hierarchies in multilevel Monte Carlo samplers

Low-rank tensor approximation for high-order correlation functions of Gaussian random fields

Perturbation analysis for the Darcy problem with log-normal permeability

Convergence of quasi-optimal Stochastic Galerkin methods for a class of PDES with random coefficients