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  • Bayesian D-Optimal Designs for Gaussian Process Surrogate Models
    In this work, we propose a novel initial design maximizing the Bayesian D-optimality criterion of the Gaussian process lengthscale parameter Previously published results have shown the emphasis on lengthscale estimation to be promising, but relied on an empirically driven design creation process
  • Bayesian D-Optimal Designs for Gaussian Process Surrogate Models
    In this work, we propose a novel initial design maximizing the Bayesian D-Optimality criterion of the Gaussian process lengthscale parameter Previously pub-lished results have shown the emphasis on lengthscale estimation to be promising, but relied on an empirically driven design creation process
  • Bayesian D‐Optimal Designs for Gaussian Process Surrogate Models
    In this work, we propose a novel initial design maximizing the Bayesian D‐optimality criterion of the Gaussian process lengthscale parameter Previously published results have shown the
  • Bayesian D‐Optimal Designs for Gaussian Process Surrogate Models
    In this work, we propose a novel initial design maximizing the Bayesian D-optimality criterion of the Gaussian process lengthscale parameter Previously published results have shown the emphasis on lengthscale estimation to be promising, but relied on an empirically driven design creation process
  • Bayesian D‐Optimal Designs for Gaussian Process Surrogate Models
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  • ‪Boya Zhang‬ - ‪Google Scholar‬
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