49 citations · 79 across the 11 of their papers we have counts for
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cond-mat.mtrl-sci2019★ 6 cited
Active-learning-based efficient prediction of ab-initio atomic energy: a case study on a Fe random grain boundary model with millions of atoms
Tomoyuki Tamura, Masayuki Karasuyama
We have developed a method that can analyze large random grain boundary (GB) models with the accuracy of density functional theory (DFT) calculations using active learning. It is a…
cs.LG2019★ 13 cited
Multi-objective Bayesian Optimization using Pareto-frontier Entropy
Shinya Suzuki, Shion Takeno, Tomoyuki Tamura +2
This paper studies an entropy-based multi-objective Bayesian optimization (MBO). The entropy search is successful approach to Bayesian optimization. However, for MBO, existing entr…