# Introduction to Uncertainty Quantification

- 61 Citations
- 27 Mentions
- 71k Downloads

Part of the Texts in Applied Mathematics book series (TAM, volume 63)

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Textbook

- 61 Citations
- 27 Mentions
- 71k Downloads

Part of the Texts in Applied Mathematics book series (TAM, volume 63)

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 quantification are defined, and an overview of the range of mathematical methods by which they can be achieved. Complete with exercises throughout, the book will equip readers with both theoretical understanding and practical experience of the key mathematical and algorithmic tools underlying the treatment of uncertainty in modern applied mathematics. Students and readers alike are encouraged to apply the mathematical methods discussed in this book to their own favourite problems to understand their strengths and weaknesses, also making the text suitable as a self-study. This text is designed as an introduction to uncertainty quantification for senior undergraduate and graduate students with a mathematical or statistical background, and also for researchers from the mathematical sciences or from applications areas who are interested in the field.

**T. J. Sullivan** was Warwick Zeeman Lecturer at the Mathematics Institute of the University of Warwick, United Kingdom, from 2012 to 2015. Since 2015, he is Junior Professor of Applied Mathematics at the Free University of Berlin, Germany, with specialism in Uncertainty and Risk Quantification.

Computational probability Distributional robustness Inverse Problems Model order reduction Sensitivity analysis Spectral expansions Uncertainty Quantification

- DOI https://doi.org/10.1007/978-3-319-23395-6
- Copyright Information Springer International Publishing Switzerland 2015
- Publisher Name Springer, Cham
- eBook Packages Mathematics and Statistics Mathematics and Statistics (R0)
- Print ISBN 978-3-319-23394-9
- Online ISBN 978-3-319-23395-6
- Series Print ISSN 0939-2475
- Series Online ISSN 2196-9949
- Buy this book on publisher's site