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Distance-Distributed Design for Gaussian Process Surrogates
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Distance-Distributed Design for Gaussian Process Surrogates (2019)Distance-Distributed Design for Gaussian …Replication or Exploration? Sequential Design for Stochastic Simulation Experiments (2018)Replication or Exploration? S…A NEW AND FLEXIBLE METHOD FOR CONSTRUCTING DESIGNS FOR COMPUTER EXPERIMENTS (2016)A NEW AND FLEXIBLE METHOD FOR…Handbook of Design and Analysis of Experiments (2015)Handbook of Design and Analys…Design of computer experiments: space filling and beyond (2011)Design of computer experiment…Convergence rates of efficient global optimization algorithms (2011)Convergence rates of efficien…Batch sequential designs for computer experiments (2009)Batch sequential designs for …Adaptive Design and Analysis of Supercomputer Experiments (2009)Adaptive Design and Analysis …Global Sensitivity Analysis. The Primer (2007)Global Sensitivity Analysis. …Optimal network design for spatial prediction, covariance parameter estimation, and empirical prediction (2006)Optimal network design for sp…Combining Field Data and Computer Simulations for Calibration and Prediction (2004)Combining Field Data and Comp…The Design and Analysis of Computer Experiments (2003)The Design and Analysis of Co…Exploratory designs for computational experiments (1995)Exploratory designs for compu…Minimax and maximin distance designs (1990)Minimax and maximin distance …Design and Analysis of Computer Experiments (1989)Design and Analysis of Comput…Fitting variogram models by weighted least squares (1985)Fitting variogram models by w…Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)Comparison of Three Methods f…A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (1979)A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code (2000)Choosing the Sample Size of a Computer Experiment: A Practical Guide (2009)STATISTICS FOR SPATIAL DATA (1992)A Tutorial on Latin Hypercube Design of Experiments (2015)Decision-Making in Agent-Based Models of Migration: State of the Art and Challenges (2016)Design of computer experiments: A review (2017)A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning (2010)Information-Theoretic Regret Bounds for Gaussian Process Optimization in the Bandit Setting (2012)Bayesian Optimization in a Billion Dimensions via Random Embeddings (2016)Constrained Bayesian Optimization with Noisy Experiments (2018)Bayesian optimization with safety constraints: safe and automatic parameter tuning in robotics (2021)Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index (2009)Sensitivity analysis of environmental models: A systematic review with practical workflow (2016)SALib: An open-source Python library for Sensitivity Analysis (2017)Nonparametric Estimation of Nonstationary Spatial Covariance Structure (1992)Spatial data analysis: theory and practice (2004)Fixed Rank Kriging for Very Large Spatial Data Sets (2008)Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems (2003)Taking the Human Out of the Loop: A Review of Bayesian Optimization (2015)An efficient algorithm for constructing optimal design of computer experiments (2004)Response Surface Methodology: A Retrospective and Literature Survey (2004)A Framework for Validation of Computer Models (2007)Quantification of Model Uncertainty: Calibration, Model Discrepancy, and Identifiability (2012)A distribution-free approach to inducing rank correlation among input variables (1982)Factorial Sampling Plans for Preliminary Computational Experiments (1991)Uniform Design: Theory and Application (2000)An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach (2011)A Review on Global Sensitivity Analysis Methods (2015)Sensitivity analysis: A review of recent advances (2015)
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References

  • 1989Design and Analysis of Computer Experiments6,958 cited
  • 2007Global Sensitivity Analysis. The Primer6,425 cited
  • 1979Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code3,238 cited
  • 2003The Design and Analysis of Computer Experiments2,204 cited
  • 1990Minimax and maximin distance designs1,452 cited
  • 1995Exploratory designs for computational experiments1,202 cited
  • 1985Fitting variogram models by weighted least squares1,061 cited
  • 2004Combining Field Data and Computer Simulations for Calibration and Prediction622 cited
  • 2011Convergence rates of efficient global optimization algorithms454 cited
  • 2011Design of computer experiments: space filling and beyond361 cited
  • 2015Handbook of Design and Analysis of Experiments309 cited
  • 2009Adaptive Design and Analysis of Supercomputer Experiments239 cited
  • 2006Optimal network design for spatial prediction, covariance parameter estimation, and empirical prediction172 cited
  • 2018Replication or Exploration? Sequential Design for Stochastic Simulation Experiments106 cited
  • 2009Batch sequential designs for computer experiments105 cited

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  • 2016A NEW AND FLEXIBLE METHOD FOR CONSTRUCTING DESIGNS FOR COMPUTER EXPERIMENTS90 cited
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