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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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Publication type Article: Journal article
Document type Other: News Item
Corresponding Author
ISSN (print) / ISBN 0166-4328
e-ISSN 1872-7549
Journal Behavioural Brain Research
Quellenangaben Volume: 47, Issue: , Pages: , Article Number: e170 Supplement: ,
Publisher Elsevier
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Helmholtz Artifical Intelligence Cooperation Unit (HAICU)