
Rare event estimation using stochastic spectral embedding
Estimating the probability of rare failure events is an essential step i...
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A generalized framework for active learning reliability: survey and benchmark
Active learning methods have recently surged in the literature due to th...
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A twolevel Krigingbased approach with active learning for solving timevariant risk optimization problems
Several methods have been proposed in the literature to solve reliabilit...
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Emulation of stochastic simulators using generalized lambda models
Computer simulations are used in virtually all fields of applied science...
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Bayesian model inversion using stochastic spectral embedding
In this paper we propose a new samplingfree approach to solve Bayesian ...
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Global sensitivity analysis for stochastic simulators based on generalized lambda surrogate models
Global sensitivity analysis aims at quantifying the impact of input vari...
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Stochastic spectral embedding
Constructing approximations that can accurately mimic the behavior of co...
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Replicationbased emulation of the response distribution of stochastic simulators using generalized lambda distributions
Due to limited computational power, performing uncertainty quantificatio...
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Bayesian calibration and sensitivity analysis of heat transfer models for fire insulation panels
A common approach to assess the performance of fire insulation panels is...
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Heat transfer models for fire insulation panels: Bayesian calibration and sensitivity analysis
A common approach to assess the performance of fire insulation panels is...
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Surrogateassisted reliabilitybased design optimization: a survey and a new general framework
Reliabilitybased design optimization (RBDO) is an active field of resea...
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Extending classical surrogate modelling to ultrahigh dimensional problems through supervised dimensionality reduction: a datadriven approach
Thanks to their versatility, ease of deployment and highperformance, su...
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Surrogate modeling based on resampled polynomial chaos expansions
In surrogate modeling, polynomial chaos expansion (PCE) is popularly uti...
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Datadriven polynomial chaos expansion for machine learning regression
We present a regression technique for data driven problems based on poly...
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Development of probabilistic dam breach model using Bayesian inference
Dam breach models are commonly used to predict outflow hydrographs of po...
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Gaussian process modelling using UQLab
We introduce the Gaussian process modelling module of the UQLab software...
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A general framework for uncertainty quantification under nonGaussian input dependencies
Uncertainty quantification (UQ) deals with the estimation of statistics ...
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Hierarchical Kriging for multifidelity aeroservoelastic simulators  Application to extreme loads on wind turbines
In the present work, we consider multifidelity surrogate modelling to f...
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PolynomialChaosbased Kriging
Computer simulation has become the standard tool in many engineering fie...
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Metamodelbased importance sampling for structural reliability analysis
Structural reliability methods aim at computing the probability of failu...
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Reliabilitybased design optimization using kriging surrogates and subset simulation
The aim of the present paper is to develop a strategy for solving reliab...
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Metamodelbased importance sampling for the simulation of rare events
In the field of structural reliability, the MonteCarlo estimator is con...
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B. Sudret
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