Author

Davide Noè

Tohoku University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

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Neuroscience· 1

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Research Focus:benchmarking· 1 Approach:statistical model· 1

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Hideaki YamamotoiD· 1 shared Shigeo SatoiD· 1 shared Yuichi KatoriiD· 1 shared

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2025-2025 · peak 1/yr

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1 shared paperNeuroscience

Hideaki YamamotoORCID

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1 paper

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NeurosciencebioRxivPreprintMay 25, 2025

Efficient learning and intrinsic noise filtering in recurrent spiking neural networks trained with e-prop

Davide Noè, Hideaki Yamamoto, Yuichi Katori, Shigeo Sato

This study examines how e-prop learning performs in recurrent spiking neural networks under varying connectivity and noise levels, finding that sparsity improves learning by enhancing activation diversity.

DOI 10.1101/2025.05.25.656058

statistical modelbenchmarking

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