Quantification of Uncertainty: Improving Efficiency and Technology
Springer Nature Switzerland AG, 2020
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This book explores four guiding themes – reduced order modelling, high dimensional problems, efficient algorithms, and applications – by reviewing recent algorithmic and mathematical advances and the development of new research directions for uncertainty quantification in the context of partial differential equations with random inputs.
- ISBN-13
- 9783030487201
- ISBN-10
- 3030487202
- Publisher
- Springer Nature Switzerland AG
- Year
- 2020
- Publication date
- 2020-07-31
- Pages
- 282
- Dimensions
- 235x155x