Living Reference Work

Continuously updated edition

Handbook of Uncertainty Quantification

Editors:

ISBN: 978-3-319-11259-6 (Print) 978-3-319-11259-6 (Online)

Table of contents (58 entries)

A - Z
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  1. All

  2. B

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      Bayes Linear Emulation, History Matching, and Forecasting for Complex Computer Simulators

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      Bayesian Cubic Spline in Computer Experiments

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      Bayesian Uncertainty Propagation Using Gaussian Processes

  3. C

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      COSSAN: A Multidisciplinary Software Suite for Uncertainty Quantification and Risk Management

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      Compressive Sampling Methods for Sparse Polynomial Chaos Expansions

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      Conceptual Structure of Performance Assessments for Geologic Disposal of Radioactive Waste

  4. D

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      Dakota: Bridging Advanced Scalable Uncertainty Quantification Algorithms with Production Deployment

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      Decision Analytic and Bayesian Uncertainty Quantification for Decision Support

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      Derivative-Based Global Sensitivity Measures

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      Design of Experiments for Screening

  5. E

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      Embedded Uncertainty Quantification Methods via Stokhos

  6. G

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      Gaussian Process-Based Sensitivity Analysis and Bayesian Model Calibration with GPMSA

  7. H

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      Hierarchical Models for Uncertainty Quantification: An Overview

  8. I

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      Inference Given Summary Statistics

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      Introduction to Sensitivity Analysis

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      Introduction to Uncertainty Quantification

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      Intrusive Polynomial Chaos Methods for Forward Uncertainty Propagation

  9. L

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      Low-Rank Tensor Methods for Model Order Reduction

  10. M

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      Maximin Sliced Latin Hypercube Designs with Application to Cross Validating Prediction Error

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      Metamodel-Based Sensitivity Analysis: Polynomial Chaos Expansions and Gaussian Processes

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