Extrapolative Bayesian optimization with Gaussian process and neural network ensemble surrogate models

• Main Authors: Lim, Yee-Fun, Ng, Chee Koon, Vaitesswar, U. S., Hippalgaonkar, Kedar
• 其他作者: School of Materials Science and Engineering
• 格式: Article
• 語言: English
• 出版: 2022
• 主題: Engineering::Materials; Automated Experiments; Bayesian Optimization
• 在線閱讀: https://hdl.handle.net/10356/159296

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...