2 citations · 2 across the 5 of their papers we have counts for
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Bayesian optimization with kernel ensembles and disagreement-based acquisition for source localization and acoustic inversion
Heng Zhang, Haotian Xiang, Florian Meyer +1
Joint source localization and geoacoustic inversion requires optimizing an objective built from an expensive normal mode propagation model. Bayesian optimization (BO) with a Gaussi…
Enhancing Bayesian Optimization and Active Learning Through Kernel Diversity
Heng Zhang, Haotian Xiang, Konstantinos D. Polyzos +2
Hyperparameter selection remains a key challenge in Bayesian optimization (BO) and Bayesian active learning (AL), as model misspecification can lead to suboptimal performance, whil…
Scalable Variational Bayesian Fine-Tuning of LLMs via Orthogonalized Low-Rank Adapters
Haotian Xiang, Bingcong Li, Qin Lu
When deploying large language models (LLMs) to safety-critical applications, uncertainty quantification (UQ) is of utmost importance to self-assess the reliability of the LLM-based…
Fine-tuning LLMs with variational Bayesian last layer for high-dimensional Bayesian optimization
Haotian Xiang, Jinwen Xu, Qin Lu
A plethora of applications entail solving black-box optimization problems with high evaluation costs, including drug discovery, material design, as well as hyperparameter tuning. T…