Pessimistic asynchronous sampling in high-cost Bayesian optimization

Digital Discovery 2026 Open access

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Authors: Amanda A. Volk, Kristofer Reyes, Jeffrey G. Ethier, Luke A. Baldwin
DOI: 10.1039/d5dd00477b
Cited by: 0
References: 16

Abstract

Pessimistic model predictions in asynchronous Bayesian optimization can enable more efficient and robust experimental system optimization in both asychronous and serial sampling settings.

Fields of Study & Subjects

Advanced Bandit Algorithms Research Optimal Experimental Design Methods Advanced Multi-Objective Optimization Algorithms

Publication details

Journal / source
Digital Discovery
Volume
5
Issue
4
Pages
1613–1622
Publication date
1 January 2026
Language
EN