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Hao-Tian Xiang

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#machine learning Preprint Sep 2026

Bayesian optimization with kernel ensembles and disagreement-based acquisition for source localization and acoustic inversion

Joint source localization and geoacoustic inversion requires optimizing an objective built from an expensive normal mode propagation model. Bayesian optimization (BO) with a Gaussian process (GP) surrogate can obtain accurate parameter estimates within a limited number of forward model evaluations, but its performance...

Heng Zhang, Hao-Tian Xiang, Florian Meyer et al. · 0 citations

#machine learning Preprint Aug 2026

Enhancing Bayesian Optimization and Active Learning Through Kernel Diversity

A unified framework, KENDO (Kernel ENsemble Disagreement-aware Operator), is proposed that integrates Ensemble Gaussian Processes (EGP) with disagreement-aware acquisition strategies and extends the approach to multi-objective optimization via random scalarization that preserves the single-optimizer conditioning struct...

Heng Zhang, Hao-Tian Xiang, Konstantinos D. Polyzos et al. · 1 citation