Introduction to Uncertainty Quantification
Uncertainty quantification is a topic of increasing practical importance at the intersection of applied mathematics, statistics, computation, and numerous application areas in science and engineering. This text provides a framework in which the main objectives of the field of uncertainty quantificat...
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| Language: | English |
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Cham :
Springer International Publishing : Imprint: Springer,
2015.
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| Edition: | 1st ed. 2015. |
| Series: | Texts in Applied Mathematics,
63 |
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| Online Access: | https://doi.org/10.1007/978-3-319-23395-6 |
Table of Contents:
- Introduction
- Measure and Probability Theory
- Banach and Hilbert Spaces
- Optimization Theory
- Measures of Information and Uncertainty
- Bayesian Inverse Problems
- Filtering and Data Assimilation
- Orthogonal Polynomials and Applications
- Numerical Integration
- Sensitivity Analysis and Model Reduction
- Spectral Expansions
- Stochastic Galerkin Methods
- Non-Intrusive Methods
- Distributional Uncertainty
- References
- Index.