34 citations · 36 across the 3 of their papers we have counts for
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cs.NE2024★ 1 cited
Elucidating the theoretical underpinnings of surrogate gradient learning in spiking neural networks
Julia Gygax, Friedemann Zenke
Training spiking neural networks to approximate universal functions is essential for studying information processing in the brain and for neuromorphic computing. Yet the binary nat…
cs.NE2022★ 34 cited
Fluctuation-driven initialization for spiking neural network training
Julian Rossbroich, Julia Gygax, Friedemann Zenke
Spiking neural networks (SNNs) underlie low-power, fault-tolerant information processing in the brain and could constitute a power-efficient alternative to conventional deep neural…