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Adaptive Kriging Stochastic Sampling and Density Approximation and Its Application to Rare-Event Estimation
16 references·8 citing·34 second hop
Adaptive Kriging Stochastic Sampling and Density Approximation and Its Application to Rare-Event Estimation (2018)Adaptive Kriging Stochastic Sampling and …Rare Event Estimation Using Polynomial-Chaos Kriging (2016)Rare Event Estimation Using P…Assessing small failure probabilities by AK–SS: An active learning method combining Kriging and Subset Simulation (2016)Assessing small failure proba…Engineering Risk Assessment with Subset Simulation (2014)Engineering Risk Assessment w…Bayesian Updating with Structural Reliability Methods (2014)Bayesian Updating with Struct…Metamodel-based importance sampling for structural reliability analysis (2013)Metamodel-based importance sa…Reliability-based design optimization using kriging surrogates and subset simulation (2011)Reliability-based design opti…Assessing small failure probabilities by combined subset simulation and Support Vector Machines (2011)Assessing small failure proba…AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation (2011)AK-MCS: An active learning re…Adaptive Designs of Experiments for Accurate Approximation of a Target Region (2010)Adaptive Designs of Experimen…Subset simulation for structural reliability sensitivity analysis (2008)Subset simulation for structu…Efficient Global Reliability Analysis for Nonlinear Implicit Performance Functions (2008)Efficient Global Reliability …Kriging metamodeling in simulation: A review (2007)Kriging metamodeling in simul…Design and Analysis of Simulation Experiments (2007)Design and Analysis of Simula…Use of Kriging Models to Approximate Deterministic Computer Models (2005)Use of Kriging Models to Appr…Estimation of small failure probabilities in high dimensions by subset simulation (2001)Estimation of small failure p…Design and Analysis of Computer Experiments (1989)Design and Analysis of Comput…Probability density evolution method for structural reliability analysis: A parallel Bayesian active learning perspective (2025)Probability density evolution…Multi-point active learning probability density evolution method (2025)Multi-point active learning p…A theoretically-consistent parallel enrichment strategy for Bayesian active learning reliability analysis (2025)A theoretically-consistent pa…An adaptive Kriging method based on K-means clustering and sampling in n-ball for structural reliability analysis (2023)An adaptive Kriging method ba…A new reliability method combining adaptive Kriging and active variance reduction using multiple importance sampling (2023)A new reliability method comb…Reducing Geometric Uncertainty in Computational Hemodynamics by Deep Learning-Assisted Parallel-Chain MCMC (2022)Reducing Geometric Uncertaint…A generalized framework for active learning reliability: survey and benchmark (2021)A generalized framework for a…Advances in Simulation-Based Uncertainty Quantification and Reliability Analysis (2019)Advances in Simulation-Based …Simulation and the Monte Carlo Method (1981)The stochastic finite element method: Past, present and future (2008)A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models (2012)The generalization of Latin hypercube sampling (2015)Simulation and the Monte Carlo Method (2016)Stochastic Finite Elements: A Spectral Approach (1991)Structural Reliability Methods (1996)LIF: A new Kriging based learning function and its application to structural reliability analysis (2016)Reliability analysis—a review and some perspectives (2001)A critical appraisal of reliability estimation procedures for high dimensions (2004)Machine learning-based methods in structural reliability analysis: A review (2021)Structural reliability under combined random load sequences (1978)Designs for Computer Experiments (1989)Probability, reliability and statistical methods in engineering design (1999)DAKOTA : a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis. Version 5.0, user's manual. (2010)STATISTICS FOR SPATIAL DATA (1992)Response Surface Methodology: Process and Product Optimization Using Designed Experiments (1996)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Calculations of Sobol indices for the Gaussian process metamodel (2008)Efficient surrogate models for reliability analysis of systems with multiple failure modes (2011)DiceKriging , DiceOptim : Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization (2012)Statistics for Spatial Data (1993)Aleatory or epistemic? Does it matter? (2008)A new surrogate modeling technique combining Kriging and polynomial chaos expansions – Application to uncertainty analysis in computational dosimetry (2015)An active-learning algorithm that combines sparse polynomial chaos expansions and bootstrap for structural reliability analysis (2018)Adaptive approaches in metamodel-based reliability analysis: A review (2020)Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)Active learning for structural reliability: Survey, general framework and benchmark (2022)Bayesian Experimental Design: A Review (1995)Sensitivity analysis: A review of recent advances (2015)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Taking the Human Out of the Loop: A Review of Bayesian Optimization (2015)POLYNOMIAL-CHAOS-BASED KRIGING (2015)
this work references cited by second hop

References

  • 1989Design and Analysis of Computer Experiments6,958 cited
  • 2001Estimation of small failure probabilities in high dimensions by subset simulation2,419 cited
  • 2011AK-MCS: An active learning reliability method combining Kriging and Monte Carlo Simulation2,048 cited
  • 2007Kriging metamodeling in simulation: A review1,278 cited
  • 2008Efficient Global Reliability Analysis for Nonlinear Implicit Performance Functions1,141 cited
  • 2005Use of Kriging Models to Approximate Deterministic Computer Models840 cited
  • 2013Metamodel-based importance sampling for structural reliability analysis535 cited
  • 2011Reliability-based design optimization using kriging surrogates and subset simulation450 cited
  • 2011Assessing small failure probabilities by combined subset simulation and Support Vector Machines419 cited
  • 2016Assessing small failure probabilities by AK–SS: An active learning method combining Kriging and Subset Simulation412 cited
  • 2014Bayesian Updating with Structural Reliability Methods339 cited
  • 2007Design and Analysis of Simulation Experiments317 cited
  • 2014Engineering Risk Assessment with Subset Simulation315 cited
  • 2010Adaptive Designs of Experiments for Accurate Approximation of a Target Region291 cited

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2008
Subset simulation for structural reliability sensitivity analysis
284 cited
  • 2016Rare Event Estimation Using Polynomial-Chaos Kriging279 cited
  • Cited by

    • 2023An adaptive Kriging method based on K-means clustering and sampling in n-ball for structural reliability analysis29 cited
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    • 2023A new reliability method combining adaptive Kriging and active variance reduction using multiple importance sampling20 cited
    • 2025Multi-point active learning probability density evolution method11 cited
    • 2021A generalized framework for active learning reliability: survey and benchmark11 cited
    • 2025Probability density evolution method for structural reliability analysis: A parallel Bayesian active learning perspective7 cited
    • 2022Reducing Geometric Uncertainty in Computational Hemodynamics by Deep Learning-Assisted Parallel-Chain MCMC7 cited
    • 2019Advances in Simulation-Based Uncertainty Quantification and Reliability Analysis7 cited