HOW CONNECTIVITY STRUCTURE SHAPES RICH AND LAZY LEARNING IN NEURAL CIRCUITS

In theoretical neuroscience, recent work leverages deep learning tools to explore how some network attributes critically influence its learning dynamics. Notably, initial weight distributions with small (resp. large) variance may yield a rich (resp. lazy) regime, where significant (resp. minor) chan...

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Detalles Bibliográficos
Autores principales: Liu, Yuhan Helena, Baratin, Aristide, Cornford, Jonathan, Mihalas, Stefan, Shea-Brown, Eric, Lajoie, Guillaume
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cornell University 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10593070/
https://www.ncbi.nlm.nih.gov/pubmed/37873007

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10593070/
https://www.ncbi.nlm.nih.gov/pubmed/37873007

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