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Analyticity and Sparsity in Uncertainty Quantification for Pdes with Gaussian Random Field Inputs
Paperback
Series: Lecture Notes in Mathematics, Book 2334
General MathematicsProbability & Statistics
ISBN13: 9783031383830
Publisher: Springer
Published: Oct 14 2023
Pages: 207
Weight: 0.70
Height: 0.47 Width: 6.14 Depth: 9.21
Language: English
The presented Algorithms and results are relevant for the mathematical analysis of many approximation methods for PDEs with GRF inputs, such as model order reduction, neural network and tensor-formatted surrogates of parametric solution families. They are expected to impact computational uncertainty quantification subject to GRF models of uncertainty in PDEs, and are of interest for researchers and graduate students in both, applied and computational mathematics, as well as in computational science and engineering.
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