JavaScript is disabled for your browser. Some features of this site may not work without it.
| dc.contributor.author | Peters, Jan | |
| dc.date.accessioned | 2021-03-24T14:53:44Z | |
| dc.date.available | 2021-03-24T14:53:44Z | |
| dc.date.issued | 2020 | |
| dc.identifier.issn | 2522-5839 | |
| dc.identifier.uri | http://hdl.handle.net/10900/113593 | |
| dc.language.iso | en | en |
| dc.publisher | Springernature | de_DE |
| dc.relation.uri | http://dx.doi.org/10.1038/s42256-020-00255-1 | |
| dc.subject.ddc | 004 | de_DE |
| dc.title | Evolutionary training and abstraction yields algorithmic generalization of neural computers | de_DE |
| dc.type | Article | de_DE |
| utue.quellen.id | 20210304112512_00590 | |
| utue.personen.roh | Tanneberg, Daniel | |
| utue.personen.roh | Rueckert, Elmar | |
| utue.personen.roh | Peters, Jan | |
| dcterms.isPartOf.ZSTitelID | Nature Machine Intelligence | de_DE |
| dcterms.isPartOf.ZS-Issue | 12 | de_DE |
| dcterms.isPartOf.ZS-Volume | 2 | de_DE |
| utue.fakultaet | Sonstige |
Dateien zu dieser Ressource
| Dateien | Größe | Format | Anzeige |
|---|---|---|---|
|
Zu diesem Dokument gibt es keine Dateien. |
|||