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Binz, M. ; Dasgupta, I.* ; Jagadish, A.K. ; Botvinick, M.* ; Wang, J.X.* ; Schulz, E.

Meta-learning: Data, architecture, and both.

Behav. Brain Res. 47:e170 (2024)
DOI PMC
We are encouraged by the many positive commentaries on our target article. In this response, we recapitulate some of the points raised and identify synergies between them. We have arranged our response based on the tension between data and architecture that arises in the meta-learning framework. We additionally provide a short discussion that touches upon connections to foundation models.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Sonstiges: Nachrichtenmeldung
Korrespondenzautor
ISSN (print) / ISBN 0166-4328
e-ISSN 1872-7549
Zeitschrift Behavioural Brain Research
Quellenangaben Band: 47, Heft: , Seiten: , Artikelnummer: e170 Supplement: ,
Verlag Elsevier
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Helmholtz Artifical Intelligence Cooperation Unit (HAICU)