An Empirical Interpolation and Model-Variance Reduction Method for Computing Statistical Outputs of Parametrized Stochastic Partial Differential Equations
DOI10.1137/15M1016783zbMath1386.65044MaRDI QIDQ5741177
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Publication date: 22 July 2016
Published in: SIAM/ASA Journal on Uncertainty Quantification (Search for Journal in Brave)
stochastic optimizationmodel reductionreduced basis methodvariance reductiona posteriori error estimationempirical interpolation methodhybridizable discontinuous Galerkin methodmultilevel Monte Carlo methodstochastic elliptic parametrized PDEs
Monte Carlo methods (65C05) Boundary value problems for second-order elliptic equations (35J25) Applications of stochastic analysis (to PDEs, etc.) (60H30) Finite element, Rayleigh-Ritz and Galerkin methods for initial value and initial-boundary value problems involving PDEs (65M60) PDEs with randomness, stochastic partial differential equations (35R60) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30) Variational methods for second-order elliptic equations (35J20)
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