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Neural networks with optimized single-neuron adaptation uncover biologically plausible regularization
View ORCID ProfileVictor Geadah, View ORCID ProfileStefan Horoi, Giancarlo Kerg, View ORCID ProfileGuy Wolf, View ORCID ProfileGuillaume Lajoie
doi: https://doi.org/10.1101/2022.04.29.489963
Victor Geadah
1Program in Applied and Computational Mathematics, Princeton University, Princeton, U.S.A.
2Mila - Quebec Artificial Intelligence Institute, Montréal, Canada
3Département de Mathématiques et Statistiques, Université de Montréal, Montréal, Canada
Stefan Horoi
2Mila - Quebec Artificial Intelligence Institute, Montréal, Canada
3Département de Mathématiques et Statistiques, Université de Montréal, Montréal, Canada
Giancarlo Kerg
2Mila - Quebec Artificial Intelligence Institute, Montréal, Canada
4Département d’Informatique et Recherche Opérationelle, Université de Montréal, Montréal, Canada
Guy Wolf
2Mila - Quebec Artificial Intelligence Institute, Montréal, Canada
3Département de Mathématiques et Statistiques, Université de Montréal, Montréal, Canada
5Canada CIFAR AI Chair
Guillaume Lajoie
2Mila - Quebec Artificial Intelligence Institute, Montréal, Canada
3Département de Mathématiques et Statistiques, Université de Montréal, Montréal, Canada
5Canada CIFAR AI Chair
Posted July 19, 2023.
Neural networks with optimized single-neuron adaptation uncover biologically plausible regularization
Victor Geadah, Stefan Horoi, Giancarlo Kerg, Guy Wolf, Guillaume Lajoie
bioRxiv 2022.04.29.489963; doi: https://doi.org/10.1101/2022.04.29.489963
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