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Seko, Atsuto, Hayashi, Hiroyuki, Nakayama, Keita, Takahashi, Akira, Tanaka, Isao (2017) Representation of compounds for machine-learning prediction of physical properties. Physical Review B, 95 (14) doi:10.1103/physrevb.95.144110

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Reference TypeJournal (article/letter/editorial)
TitleRepresentation of compounds for machine-learning prediction of physical properties
JournalPhysical Review B
AuthorsSeko, AtsutoAuthor
Hayashi, HiroyukiAuthor
Nakayama, KeitaAuthor
Takahashi, AkiraAuthor
Tanaka, IsaoAuthor
Year2017 (April 19)Volume95
Issue14
PublisherAmerican Physical Society (APS)
DOIdoi:10.1103/physrevb.95.144110Search in ResearchGate
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Mindat Ref. ID14245512Long-form Identifiermindat:1:5:14245512:0
GUID0
Full ReferenceSeko, Atsuto, Hayashi, Hiroyuki, Nakayama, Keita, Takahashi, Akira, Tanaka, Isao (2017) Representation of compounds for machine-learning prediction of physical properties. Physical Review B, 95 (14) doi:10.1103/physrevb.95.144110
Plain TextSeko, Atsuto, Hayashi, Hiroyuki, Nakayama, Keita, Takahashi, Akira, Tanaka, Isao (2017) Representation of compounds for machine-learning prediction of physical properties. Physical Review B, 95 (14) doi:10.1103/physrevb.95.144110
In(2017, April) Physical Review B Vol. 95 (14) American Physical Society (APS)

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Lee, Joohwi, Seko, Atsuto, Shitara, Kazuki, Nakayama, Keita, Tanaka, Isao (2016) Prediction model of band gap for inorganic compounds by combination of density functional theory calculations and machine learning techniques. Physical Review B, 93 (11) doi:10.1103/physrevb.93.115104
Seko, Atsuto, Takahashi, Akira, Tanaka, Isao (2014) Sparse representation for a potential energy surface. Physical Review B, 90 (2) doi:10.1103/physrevb.90.024101
Seko, Atsuto, Takahashi, Akira, Tanaka, Isao (2015) First-principles interatomic potentials for ten elemental metals via compressed sensing. Physical Review B, 92 (5) doi:10.1103/physrevb.92.054113
Seko, Atsuto, Togo, Atsushi, Tanaka, Isao (2019) Group-theoretical high-order rotational invariants for structural representations: Application to linearized machine learning interatomic potential. Physical Review B, 99 (21) doi:10.1103/physrevb.99.214108
Seko, Atsuto, Togo, Atsushi, Hayashi, Hiroyuki, Tsuda, Koji, Chaput, Laurent, Tanaka, Isao (2015) Prediction of Low-Thermal-Conductivity Compounds with First-Principles Anharmonic Lattice-Dynamics Calculations and Bayesian Optimization. Physical Review Letters, 115 (20). doi:10.1103/physrevlett.115.205901
Hayashi, Hiroyuki, Hayashi, Katsuyuki, Kouzai, Keita, Seko, Atsuto, Tanaka, Isao (2019) Recommender System of Successful Processing Conditions for New Compounds Based on a Parallel Experimental Data Set. Chemistry of Materials, 31. 9984-9992 doi:10.1021/acs.chemmater.9b01799
Ikeda, Yuji, Carreras, Abel, Seko, Atsuto, Togo, Atsushi, Tanaka, Isao (2017) Mode decomposition based on crystallographic symmetry in the band-unfolding method. Physical Review B, 95 (2) doi:10.1103/physrevb.95.024305
Seko, Atsuto, Tanaka, Isao (2015) Special quasirandom structure in heterovalent ionic systems. Physical Review B, 91 (2) doi:10.1103/physrevb.91.024106
Seko, Atsuto, Maekawa, Tomoya, Tsuda, Koji, Tanaka, Isao (2014) Machine learning with systematic density-functional theory calculations: Application to melting temperatures of single- and binary-component solids. Physical Review B, 89 (5) doi:10.1103/physrevb.89.054303
Hayashi, Hiroyuki, Seko, Atsuto, Tanaka, Isao (2022) Recommender system for discovery of inorganic compounds. npj Computational Materials, 8 (1). doi:10.1038/s41524-022-00899-0
Seko, Atsuto, Shitara, Kazuki, Tanaka, Isao (2014) Efficient determination of alloy ground-state structures. Physical Review B, 90 (17) doi:10.1103/physrevb.90.174104
 
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