A Bayesian latent GP calibration framework for aerodynamic surrogates marginalizes input uncertainty and matches output uncertainty statistics, achieving 94.2-95.8% coverage of true 95% intervals.
Lookahead acquisition functions for finite-horizon time-dependent bayesian optimization and application to quantum optimal control.arXiv preprint arXiv:2105.09824, 2021
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A Bayesian latent Gaussian process framework for aerodynamic uncertainty quantification
A Bayesian latent GP calibration framework for aerodynamic surrogates marginalizes input uncertainty and matches output uncertainty statistics, achieving 94.2-95.8% coverage of true 95% intervals.