dc.contributor.author |
Lin, Shang-Chun |
|
dc.contributor.author |
Oettel, Martin |
|
dc.date.accessioned |
2020-07-15T12:51:35Z |
|
dc.date.available |
2020-07-15T12:51:35Z |
|
dc.date.issued |
2019 |
|
dc.identifier.issn |
2542-4653 |
|
dc.identifier.uri |
http://hdl.handle.net/10900/103260 |
|
dc.language.iso |
en |
de_DE |
dc.publisher |
Scipost Foundation |
de_DE |
dc.relation.uri |
http://dx.doi.org/10.21468/SciPostPhys.6.2.025 |
de_DE |
dc.subject.ddc |
530 |
de_DE |
dc.title |
A classical density functional from machine learning and a convolutional neural network |
de_DE |
dc.type |
Article |
de_DE |
utue.quellen.id |
20200409032300_01965 |
|
utue.personen.roh |
Lin, Shang-Chun |
|
utue.personen.roh |
Oettel, Martin |
|
dcterms.isPartOf.ZSTitelID |
Scipost Physics |
de_DE |
dcterms.isPartOf.ZS-Issue |
Article 025 |
de_DE |
dcterms.isPartOf.ZS-Volume |
6 |
de_DE |
utue.fakultaet |
07 Mathematisch-Naturwissenschaftliche Fakultät |
de_DE |