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A Weighted Reduced Basis Method For Elliptic 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 Weighted Reduced Basis Method For Elliptic Partial Differential Equations With Random Input Data

Graph Chatbot

Chattez avec Graph Search

Mimetic scalar products of discrete differential forms

Spectral and High Order Methods for Partial Differential Equations - ICOSAHOM 2012

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

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Kantorovich distance in the martingale CLT and quantitative homogenization of parabolic equations with random coefficients

Accurate and efficient evaluation of failure probability for partial different equations with random input data

BPX-preconditioning for isogeometric analysis

Spectral and High Order Methods for Partial Differential Equations - ICOSAHOM 2012

BPX-preconditioning for isogeometric analysis

MATHICSE Technical Report : A multi level Monte Carlo method with control variate for elliptic PDEs with log-normal coefficients

Mimetic scalar products of discrete differential forms

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

Kantorovich distance in the martingale CLT and quantitative homogenization of parabolic equations with random coefficients

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

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

Accurate and efficient evaluation of failure probability for partial different equations with random input data

Interface control domain decomposition methods for heterogeneous problems