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Novel algorithm using Active Metamodel Learning and Importance Sampling: application to multiple failure regions of low probability

Nassim Razaaly 1, 2 Pietro Marco Congedo 3, 2
1 CARDAMOM - Certified Adaptive discRete moDels for robust simulAtions of CoMplex flOws with Moving fronts
IMB - Institut de Mathématiques de Bordeaux, Inria Bordeaux - Sud-Ouest
2 Inria-CWI - Inria-CWI
3 DeFI - Shape reconstruction and identification
Inria Saclay - Ile de France, CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique
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Journal articles
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https://hal.inria.fr/hal-01780050
Contributor : Pietro Marco Congedo Connect in order to contact the contributor
Submitted on : Friday, April 27, 2018 - 10:40:58 AM
Last modification on : Tuesday, October 19, 2021 - 11:06:03 PM

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  • HAL Id : hal-01780050, version 1

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CNRS | X-CMAP | CMAP | X | INRIA-CWI | INRIA | X-DEP-MATHA | IMB | GS-COMPUTER-SCIENCE

Citation

Nassim Razaaly, Pietro Marco Congedo. Novel algorithm using Active Metamodel Learning and Importance Sampling: application to multiple failure regions of low probability. Journal of Computational Physics, Elsevier, In press. ⟨hal-01780050⟩

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