Media type: E-Book Title: Development and Application of Machine Learning Methods to Selected Problems of Theoretical Solid State Physics Contributor: Hoock, Benedikt [Verfasser]; Draxl, Claudia [Gutachter]; Vybíral, Jan [Gutachter]; Leser, Ulf [Gutachter] imprint: Berlin: Humboldt-Universität zu Berlin, 2022 Extent: Online-Ressource Language: English DOI: 10.18452/24919 Identifier: Keywords: Machine learning ; Solid state physics ; Maschinelles Lernen ; LASSO ; SISSO ; Gitterkonstante ; Mischungsenergie ; ternäre Gruppe-IV Legierungen ; symbolische Regression ; Deskriptor ; computergestützte Festkörperphysik ; Machine Learning ; lattice constant ; energy of mixing ; group-IV ternary compounds ; symbolic regression ; descriptor ; computational materials science Origination: University thesis: Dissertation, Berlin, Humboldt-Universität zu Berlin, 2022 Footnote: Access State: Open Access