SISSO: A compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates

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SISSO: A compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates

Ouyang, R., Curtarolo, S., Ahmetcik, E., Scheffler, M., & Ghiringhelli, L. M. (2018). SISSO: A compressed-sensing method for identifying the best low-dimensional descriptor in an immensity of offered candidates. Physical Review Materials, 2: 083802. doi:10.1103/PhysRevMaterials.2.083802.

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Datum des Verwerfens: 2019-08-07

Kommentar: Dublette bigmax

Urheber:
Ouyang, Runhai¹
Curtarolo, Stefano^{1, 2}
Ahmetcik, Emre¹
Scheffler, Matthias¹
Ghiringhelli, Luca M.¹

Affiliations:
1Theory, Fritz Haber Institute, Max Planck Society, ou_634547
2Duke University, Durham, North Carolina, USA, ou_persistent22

Datum: Erschienen: 2018

Dateien: 0 Dateien

Externe Referenzen: 0 ext. Referenzen

Versions ID: item_3005403_3

Status des Datensatzes: Verworfen

Name des Kontextes: External Context of the Max Planck Institute for Dynamics of Complex Technical Systems, Zugehörig zu: Max Planck Institute for Dynamics of Complex Technical Systems