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Isotropic Gaussian Processes Improve Vanilla Bayesian Optimization in High Dimensions

arXiv:2610.05780v1 Announce Type: new Abstract: High-dimensional Bayesian optimization (BO) often fits Gaussian process (GP) surrogates from far fewer observations than input dimensions. Modern Vanilla BO can perform well in this regime with dimension-aware priors, initialization, and acquisition o…

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  1. 2026-10-06 04:00 · arXiv stat.ML
    Isotropic Gaussian Processes Improve Vanilla Bayesian Optimization in High Dimensions

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