Neither hype nor gloom do DNNs justice.


Journal

The Behavioral and brain sciences
ISSN: 1469-1825
Titre abrégé: Behav Brain Sci
Pays: England
ID NLM: 7808666

Informations de publication

Date de publication:
06 Dec 2023
Historique:
medline: 7 12 2023
pubmed: 6 12 2023
entrez: 6 12 2023
Statut: epublish

Résumé

Neither the hype exemplified in some exaggerated claims about deep neural networks (DNNs), nor the gloom expressed by Bowers et al. do DNNs as models in vision science justice: DNNs rapidly evolve, and today's limitations are often tomorrow's successes. In addition, providing explanations as well as prediction and image-computability are model desiderata; one should not be favoured at the expense of the other.

Identifiants

pubmed: 38054281
doi: 10.1017/S0140525X23001711
pii: S0140525X23001711
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e412

Auteurs

Felix A Wichmann (FA)

Neural Information Processing Group, University of Tübingen, Tübingen, Germany felix.wichmann@tuebingen.de.

Simon Kornblith (S)

Google Research, Brain Team, Toronto, ON, Canada skornblith@google.com geirhos@google.com.

Robert Geirhos (R)

Google Research, Brain Team, Toronto, ON, Canada skornblith@google.com geirhos@google.com.

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