474 citations · 2.3k across the 36 of their papers we have counts for
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cond-mat.mtrl-sci2016★ 318 cited
Representation of compounds for machine-learning prediction of physical properties
Atsuto Seko, Hiroyuki Hayashi, Keita Nakayama +2
The representations of a compound, called "descriptors" or "features", play an essential role in constructing a machine-learning model of its physical properties. In this study, we…
cond-mat.mtrl-sci2016★ 77 cited
Mode-decomposition based on crystallographic symmetry in the band-unfolding method
Yuji Ikeda, Abel Carreras, Atsuto Seko +2
The band-unfolding method is widely used to calculate the effective band structures of a disordered system from its supercell model. The unfolded band structures show the crystallo…