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Active learning for structural reliability: survey, general framework
  and benchmark
v1v2 (latest)

Active learning for structural reliability: survey, general framework and benchmark

Structural Safety (Struct. Saf.), 2021
3 June 2021
M. Moustapha
S. Marelli
Bruno Sudret
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Active learning for structural reliability: survey, general framework and benchmark"

17 / 17 papers shown
Active Learning For Repairable Hardware Systems With Partial Coverage
Active Learning For Repairable Hardware Systems With Partial Coverage
Owen Howell
Beyza Kalkanlı
Deniz Erdoğmuş
Michael Everett
266
0
0
20 Mar 2025
Reliability analysis for non-deterministic limit-states using stochastic
  emulators
Reliability analysis for non-deterministic limit-states using stochastic emulators
Anderson V. Pires
M. Moustapha
S. Marelli
Bruno Sudret
228
2
0
18 Dec 2024
Adaptive reduced tempering For Bayesian inverse problems and rare event
  simulation
Adaptive reduced tempering For Bayesian inverse problems and rare event simulation
Frédéric Cérou
P. Héas
Mathias Rousset
269
1
0
24 Oct 2024
Robustness investigation of quality measures for the assessment of
  machine learning models
Robustness investigation of quality measures for the assessment of machine learning models
Thomas Most
Lars Graning
Sebastian Wolff
63
0
0
08 Aug 2024
Active Learning for Neural PDE Solvers
Active Learning for Neural PDE SolversInternational Conference on Learning Representations (ICLR), 2024
Daniel Musekamp
Marimuthu Kalimuthu
David Holzmüller
Makoto Takamoto
Carlos Fernandez
AI4CE
569
21
0
02 Aug 2024
A Direct Importance Sampling-based Framework for Rare Event Uncertainty
  Quantification in Non-Gaussian Spaces
A Direct Importance Sampling-based Framework for Rare Event Uncertainty Quantification in Non-Gaussian SpacesReliability Engineering & System Safety (Reliab. Eng. Syst. Saf.), 2024
Elsayed M. Eshra
Konstantinos G. Papakonstantinou
Hamed Nikbakht
199
5
0
23 May 2024
UQ state-dependent framework for seismic fragility assessment of
  industrial components
UQ state-dependent framework for seismic fragility assessment of industrial components
C. Nardin
S. Marelli
O. Bursi
B. Sudret
M. Broccardo
115
6
0
07 May 2024
Surrogate modeling for probability distribution estimation:uniform or
  adaptive design?
Surrogate modeling for probability distribution estimation:uniform or adaptive design?Reliability Engineering & System Safety (Reliab. Eng. Syst. Saf.), 2024
Maijia Su
Ziqi Wang
O. Bursi
M. Broccardo
206
9
0
10 Apr 2024
Computing conservative probabilities of rare events with surrogates
Computing conservative probabilities of rare events with surrogates
Nicolas Bousquet
318
0
0
26 Mar 2024
Reliability analysis for data-driven noisy models using active learning
Reliability analysis for data-driven noisy models using active learning
Anderson V. Pires
M. Moustapha
S. Marelli
Bruno Sudret
AI4CE
123
9
0
19 Jan 2024
A physics and data co-driven surrogate modeling method for
  high-dimensional rare event simulation
A physics and data co-driven surrogate modeling method for high-dimensional rare event simulationJournal of Computational Physics (JCP), 2023
Jianhua Xian
Ziqi Wang
AI4CE
298
14
0
30 Sep 2023
Survey of Trustworthy AI: A Meta Decision of AI
Survey of Trustworthy AI: A Meta Decision of AI
Caesar Wu
Yuan-Fang Li
Pascal Bouvry
420
3
0
01 Jun 2023
Reliability analysis of arbitrary systems based on active learning and
  global sensitivity analysis
Reliability analysis of arbitrary systems based on active learning and global sensitivity analysisReliability Engineering & System Safety (Reliab. Eng. Syst. Saf.), 2023
M. Moustapha
Pietro Parisi
S. Marelli
Bruno Sudret
172
26
0
31 May 2023
OpenAL: Evaluation and Interpretation of Active Learning Strategies
OpenAL: Evaluation and Interpretation of Active Learning Strategies
W. Jonas
A. Abraham
L. Dreyfus-Schmidt
267
1
0
11 Apr 2023
Active learning for structural reliability analysis with multiple limit
  state functions through variance-enhanced PC-Kriging surrogate models
Active learning for structural reliability analysis with multiple limit state functions through variance-enhanced PC-Kriging surrogate models
A. J.Moran
P. G. Morato
P. Rigo
AI4CE
162
2
0
23 Feb 2023
Learning non-stationary and discontinuous functions using clustering,
  classification and Gaussian process modelling
Learning non-stationary and discontinuous functions using clustering, classification and Gaussian process modelling
M. Moustapha
Bruno Sudret
144
11
0
30 Nov 2022
Hitting the Target: Stopping Active Learning at the Cost-Based Optimum
Hitting the Target: Stopping Active Learning at the Cost-Based Optimum
Zac Pullar-Strecker
Katharina Dost
E. Frank
Jörg Simon Wicker
417
17
0
07 Oct 2021
1
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