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Polynomial Chaos: Modeling, Estimation, and Approximation · Study

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ChapterPolynomial Chaos: Modeling, Estimation, and Approximation

Roger Ghanem2016

Chapter2016

Polynomial Chaos: Modeling, Estimation, and Approximation

Roger Ghanem · John Red-Horse

11 citations·0/0 files stored·Springer eBooks

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Probabilistic and Robust Engineering Design Model Reduction and Neural Networks Gaussian Processes and Bayesian Inference

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References

1991Stochastic Finite Elements: A Spectral Approach 2002The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations 2005High-Order Collocation Methods for Differential Equations with Random Inputs 2004Galerkin Finite Element Approximations of Stochastic Elliptic Partial Differential Equations 1951Multiple Wiener Integral 2004Physical Systems with Random Uncertainties: Chaos Representations with Arbitrary Probability Measure 2004Galerkin methods for linear and nonlinear elliptic stochastic partial differential equations 2002A Stochastic Projection Method for Fluid Flow

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Year2016

Typechapter

Published2016-01-01

VenueSpringer eBooks

Languageen

Citations11

Files0 public / 0

ShelfProbabilistic and Robust Engineering Design

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doi10.1007/978-3-319-11259-6_13-1

openalex_workW2563655045

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