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Variance based sensitivity analysis for Monte Carlo and importance
  sampling reliability assessment with Gaussian processes

Variance based sensitivity analysis for Monte Carlo and importance sampling reliability assessment with Gaussian processes

30 November 2020
Morgane Menz
S. Dubreuil
Jérome Morio
C. Gogu
N. Bartoli
Marie Chiron
ArXiv (abs)PDFHTML

Papers citing "Variance based sensitivity analysis for Monte Carlo and importance sampling reliability assessment with Gaussian processes"

5 / 5 papers shown
Surrogate Modeling and Explainable Artificial Intelligence for Complex Systems: A Workflow for Automated Simulation Exploration
Surrogate Modeling and Explainable Artificial Intelligence for Complex Systems: A Workflow for Automated Simulation Exploration
Paul Saves
P. Palar
M. R
Nicolas Verstaevel
Moncef Garouani
Julien Aligon
Benoît Gaudou
K. Shimoyama
J. Morlier
163
5
0
19 Oct 2025
SMT-EX: An Explainable Surrogate Modeling Toolbox for Mixed-Variables Design Exploration
SMT-EX: An Explainable Surrogate Modeling Toolbox for Mixed-Variables Design Exploration
M. R
Paul Saves
P. Palar
L. Zuhal
oseph Morlier
MoELRM
352
4
0
25 Mar 2025
SMT 2.0: A Surrogate Modeling Toolbox with a focus on Hierarchical and
  Mixed Variables Gaussian Processes
SMT 2.0: A Surrogate Modeling Toolbox with a focus on Hierarchical and Mixed Variables Gaussian ProcessesAdvances in Engineering Software (Adv. Eng. Softw.), 2023
P. Saves
R. Lafage
N. Bartoli
Y. Diouane
J. Bussemaker
T. Lefebvre
John T. Hwang
J. Morlier
J. Martins
MoE
502
125
0
23 May 2023
Uncertainty Quantification in Machine Learning for Engineering Design
  and Health Prognostics: A Tutorial
Uncertainty Quantification in Machine Learning for Engineering Design and Health Prognostics: A TutorialMechanical systems and signal processing (MSSP), 2023
V. Nemani
Luca Biggio
Xun Huan
Zhen Hu
Olga Fink
Anh Tran
Yan Wang
Xiaoge Zhang
Chao Hu
AI4CE
321
148
0
07 May 2023
Improvement of the cross-entropy method in high dimension for failure
  probability estimation through a one-dimensional projection without gradient
  estimation
Improvement of the cross-entropy method in high dimension for failure probability estimation through a one-dimensional projection without gradient estimationReliability Engineering & System Safety (RESS), 2020
Maxime El Masri
Jérome Morio
F. Simatos
436
31
0
21 Dec 2020
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