SURROGATE MODELING OF STOCHASTIC FUNCTIONS-APPLICATION TO COMPUTATIONAL ELECTROMAGNETIC DOSIMETRY

DOI10.1615/Int.J.UncertaintyQuantification.2019029103zbMath1498.62149arXiv1811.04079OpenAlexW2953685349WikidataQ127565513 ScholiaQ127565513MaRDI QIDQ5052371

Soumaya Azzi, Joe Wiart, Bruno Sudret, Yuan-Yuan Huang

Publication date: 24 November 2022

Published in: International Journal for Uncertainty Quantification (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1811.04079

Mathematics Subject Classification ID

Computational methods for problems pertaining to probability theory (60-08) Response surface designs (62K20)

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Surrogate Modeling with Gaussian Processes for an Inverse Problem in Polymer Dynamics ⋮ Risk bounds when learning infinitely many response functions by ordinary linear regression ⋮ A spectral surrogate model for stochastic simulators computed from trajectory samples ⋮ Emulation of Stochastic Simulators Using Generalized Lambda Models

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