Fostering Compositionality in Latent, Generative Encodings to Solve the Omniglot Challenge

dc.contributor.author	Fabi, Sarah
dc.contributor.author	Otte, Sebastian
dc.contributor.author	Butz, Martin V.
dc.date.accessioned	2022-04-01T15:31:16Z
dc.date.available	2022-04-01T15:31:16Z
dc.date.issued	2021
dc.identifier.isbn	978-3-030-86339-5
dc.identifier.isbn	978-3-030-86340-1
dc.identifier.uri	http://hdl.handle.net/10900/125916
dc.language.iso	en	de_DE
dc.publisher	Cham: Springer	de_DE
dc.relation.ispartofseries	Lecture Notes in Computer Science;12892
dc.relation.uri	https://doi.org/10.1007/978-3-030-86340-1_42	de_DE
dc.subject.ddc	004	de_DE
dc.title	Fostering Compositionality in Latent, Generative Encodings to Solve the Omniglot Challenge	de_DE
dc.type	BookPart	de_DE
utue.publikation.seiten	525-536	de_DE
utue.personen.roh	Fabi, Sarah
utue.personen.roh	Otte, Sebastian
utue.personen.roh	Butz, Martin V.
utue.publikation.buchdesbeitrags	Farkaš, I., Masulli, P., Otte, S., Wermter, S. (eds) Artificial Neural Networks and Machine Learning – ICANN 2021	de_DE