Extrapolative Bayesian Optimization with Gaussian Process and Neural Network Ensemble Surrogate Models

Bayesian optimization (BO) has emerged as the algorithm of choice for guiding the selection of experimental parameters in automated active learning driven high throughput experiments in materials science and chemistry. Previous studies suggest that optimization performance of the typical surrogate m...

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Autores principales: Yee-Fun Lim, Chee Koon Ng, U.S. Vaitesswar, Kedar Hippalgaonkar
Formato: article
Lenguaje:EN
Publicado: Wiley 2021
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Acceso en línea:https://doaj.org/article/7b396f6d97e843f0b445409a937ba3a1
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