The Remarkable Robustness of Surrogate Gradient Learning for Instilling Complex Function in Spiking Neural Networks

DOI10.1162/neco_a_01367OpenAlexW3124478039MaRDI QIDQ5004332

Friedemann Zenke, Tim P. Vogels

Publication date: 30 July 2021

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1162/neco_a_01367

Mathematics Subject Classification ID

Artificial intelligence (68Txx)

Related Items (1)

Heterogeneity in Neuronal Dynamics Is Learned by Gradient Descent for Temporal Processing Tasks

Uses Software

• MNIST
• PyTorch
• Adam

Cites Work

• SuperSpike: Supervised Learning in Multilayer Spiking Neural Networks
• The Vanishing Gradient Problem During Learning Recurrent Neural Nets and Problem Solutions
• Opening the Black Box: Low-Dimensional Dynamics in High-Dimensional Recurrent Neural Networks

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