The ICSCREAM methodology: Identification of penalizing configurations in
computer experiments using screening and metamodel -- Applications in
thermal-hydraulics

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The ICSCREAM methodology: Identification of penalizing configurations in computer experiments using screening and metamodel -- Applications in thermal-hydraulics

8 April 2020

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Papers citing "The ICSCREAM methodology: Identification of penalizing configurations in computer experiments using screening and metamodel -- Applications in thermal-hydraulics"

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Title
Uncertainty Quantification for Data-Driven Machine Learning Models in Nuclear Engineering Applications: Where We Are and What Do We Need? Xu Wu L. Moloko P. Bokov Gregory K. Delipei Joshua Kaizer K. Ivanov AI4CE 71 0 0 16 Mar 2025
Computing conservative probabilities of rare events with surrogates Nicolas Bousquet 65 0 0 26 Mar 2024
Nonparametric Bayesian approach for quantifying the conditional uncertainty of input parameters in chained numerical models Oumar Baldé Guillaume Damblin A. Marrel Antoine Bouloré L. Giraldi 22 2 0 03 Jul 2023
Bayesian sequential design of computer experiments for quantile set inversion Romain Ait Abdelmalek-Lomenech Julien Bect V. Chabridon E. Vázquez 18 5 0 02 Nov 2022
Model predictivity assessment: incremental test-set selection and accuracy evaluation E. Fekhari Bertrand Iooss Joseph Muré L. Pronzato M. Rendas 64 13 0 08 Jul 2022