An ensemble of hierarchical kriging emulators aggregated by Bayesian model averaging yields accurate multi-fidelity predictions with uncertainty-driven adaptive sampling that outperforms single models on benchmarks.
Cross-validation–based adaptive sampling for Gaussian process models.SIAM/ASA Journal on Uncertainty Quantification, 10(1):294–316, 2022
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An ensemble-based approach for multi-fidelity emulation and adaptive sampling
An ensemble of hierarchical kriging emulators aggregated by Bayesian model averaging yields accurate multi-fidelity predictions with uncertainty-driven adaptive sampling that outperforms single models on benchmarks.