Tutorial: Systematic development of polynomial machine learning potentials for elemental and alloy systems von Seko, Atsuto

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On-the-fly training of polynomial machine learning potentials in computing lattice thermal conductivity von Togo, Atsushi, Seko, Atsuto

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Structure and lattice thermal conductivity of grain boundaries in silicon by using machine learning potential and molecular dynamics von Fujii, Susumu, Seko, Atsuto

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Representation of compounds for machine-learning prediction of physical properties von Seko, Atsuto, Hayashi, Hiroyuki, Nakayama, Keita, Takahashi, Akira, Tanaka, Isao

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Prediction model of band gap for inorganic compounds by combination of density functional theory calculations and machine learning techniques von Lee, Joohwi, Seko, Atsuto, Shitara, Kazuki, Nakayama, Keita, Tanaka, Isao

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Linearized machine-learning interatomic potentials for non-magnetic elemental metals: Limitation of pairwise descriptors and trend of predictive power von Takahashi, Akira, Seko, Atsuto, Tanaka, Isao

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Combination of recommender system and single-particle diagnosis for accelerated discovery of novel nitrides von Koyama, Yukinori, Seko, Atsuto, Tanaka, Isao, Funahashi, Shiro, Hirosaki, Naoto

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Compositional descriptor-based recommender system for the materials discovery von Seko, Atsuto, Hayashi, Hiroyuki, Tanaka, Isao

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Projector-based efficient estimation of force constants von Seko, Atsuto, Togo, Atsushi

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Conceptual and practical bases for the high accuracy of machine learning interatomic potentials: Application to elemental titanium von Takahashi, Akira, Seko, Atsuto, Tanaka, Isao

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Application of machine learning potentials to predict grain boundary properties in fcc elemental metals von Nishiyama, Takayuki, Seko, Atsuto, Tanaka, Isao

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Recommender System of Successful Processing Conditions for New Compounds Based on a Parallel Experimental Data Set von Hayashi, Hiroyuki, Hayashi, Katsuyuki, Kouzai, Keita, Seko, Atsuto, Tanaka, Isao

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Efficient global crystal structure prediction using polynomial machine learning potential in the binary Al–Cu alloy system von Wakai, Hayato, Seko, Atsuto, Tanaka, Isao

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Global structure optimization following imaginary phonon modes accelerated by machine learning potentials in Cu, Ag, and Au von Naruse, Takuya, Seko, Atsuto, Tanaka, Isao

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Structure and stability of a homologous series of tin oxides von Seko, Atsuto, Togo, Atsushi, Oba, Fumiyasu, Tanaka, Isao

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Progress in nanoinformatics and informational materials science von Seko, Atsuto, Toyoura, Kazuaki, Muto, Shunsuke, Mizoguchi, Teruyasu, Broderick, Scott

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Fast material search of lithium ion conducting oxides using a recommender system von Suzuki, Kota, Ohura, Kosei, Seko, Atsuto, Iwamizu, Yudai, Zhao, Guowei, Hirayama, Masaaki, Tanaka, Isao, Kanno, Ryoji

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Native defects in oxide semiconductors: a density functional approach von Oba, Fumiyasu, Choi, Minseok, Togo, Atsushi, Seko, Atsuto, Tanaka, Isao

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Enumeration of nonequivalent substitutional structures using advanced data structure of binary decision diagram von Shinohara, Kohei, Seko, Atsuto, Horiyama, Takashi, Ishihata, Masakazu, Honda, Junya, Tanaka, Isao

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Mode decomposition based on crystallographic symmetry in the band-unfolding method von Ikeda, Yuji, Carreras, Abel, Seko, Atsuto, Togo, Atsushi, Tanaka, Isao

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