Towards grounding conceptual spaces in neural representations

Autor(en): Bechberger, L.
Kühnberger, K.-U. 
Herausgeber: Besold, T.R.
Noble, I.
d'Avila Garcez, A.
Stichwörter: Conceptual spaces; High dimensional spaces; Neural representations; Sub-symbolic; Unlabeled data
Erscheinungsdatum: 2017
Herausgeber: CEUR-WS
Enthalten in: CEUR Workshop Proceedings
Band: 2003
Zusammenfassung: 
The highly influential framework of conceptual spaces provides a geometric way of representing knowledge. It aims at bridging the gap between symbolic and subsymbolic processing. Instances are represented by points in a high-dimensional space and concepts are represented by convex regions in this space. In this paper, we present our approach towards grounding the dimensions of a conceptual space in latent spaces learned by an InfoGAN from unlabeled data. Copyright © 2017 for this paper by its authors.
Beschreibung: 
Conference of 12th International Workshop on Neural-Symbolic Learning and Reasoning, NeSy 2017 ; Conference Date: 17 July 2017 Through 18 July 2017; Conference Code:132032
ISSN: 16130073
Externe URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85037115832&partnerID=40&md5=12c0cdbe39a2b18bfbcc0011485527d7

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