Author

D. Noe

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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Approach:deep learning· 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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2026-2026 · peak 1/yr

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1 shared paperNeuroscience

Hideaki YamamotoORCID

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1 paper

Recent·Most cited

Predictive E-prop: A biologically inspired approach to train predictive coding-based recurrent spiking neural networks

D. Noe, Hideaki Yamamoto, Yuichi Katori, Shigeo Sato

This paper introduces Predictive E-prop, a biologically inspired model that trains recurrent spiking neural networks using gradient-based prediction error minimization, achieving self-supervised learning of complex time-series signals.

bioRxiv · Feb 15, 2026 · PreprintNeuroscience