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Uncertainty Quantification

Overview of attention for book
Cover of 'Uncertainty Quantification'

Table of Contents

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    Book Overview
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    Chapter 1 Fundamental Notions in Stochastic Modeling of Uncertainties and Their Propagation in Computational Models
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    Chapter 2 Elements of Probability Theory
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    Chapter 3 Markov Process and Stochastic Differential Equation
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    Chapter 4 MCMC Methods for Generating Realizations and for Estimating the Mathematical Expectation of Nonlinear Mappings of Random Vectors
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    Chapter 5 Fundamental Probabilistic Tools for Stochastic Modeling of Uncertainties
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    Chapter 6 Brief Overview of Stochastic Solvers for the Propagation of Uncertainties
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    Chapter 7 Fundamental Tools for Statistical Inverse Problems
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    Chapter 8 Uncertainty Quantification in Computational Structural Dynamics and Vibroacoustics
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    Chapter 9 Robust Analysis with Respect to the Uncertainties for Analysis, Updating, Optimization, and Design
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    Chapter 10 Random Fields and Uncertainty Quantification in Solid Mechanics of Continuum Media
Attention for Chapter 1: Fundamental Notions in Stochastic Modeling of Uncertainties and Their Propagation in Computational Models
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Chapter title
Fundamental Notions in Stochastic Modeling of Uncertainties and Their Propagation in Computational Models
Chapter number 1
Book title
Uncertainty Quantification
Published by
Springer, Cham, January 2017
DOI 10.1007/978-3-319-54339-0_1
Book ISBNs
978-3-31-954338-3, 978-3-31-954339-0
Authors

Christian Soize, Soize, Christian

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 50%
Unknown 1 50%
Readers by discipline Count As %
Computer Science 1 50%
Unknown 1 50%

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