279 citations · 588 across the 10 of their papers we have counts for
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cond-mat.mtrl-sci2018★ 62 cited
Efficient Construction Method for Phase Diagrams Using Uncertainty Sampling
Kei Terayama, Ryo Tamura, Yoshitaro Nose +4
We develop a method to efficiently construct phase diagrams using machine learning. Uncertainty sampling (US) in active learning is utilized to intensively sample around phase boun…
physics.chem-ph2018★ 88 cited
Population-based de novo molecule generation, using grammatical evolution
Naruki Yoshikawa, Kei Terayama, Teruki Honma +2
Automatic design with machine learning and molecular simulations has shown a remarkable ability to generate new and promising drug candidates. Current models, however, still have p…