1k citations · 2.1k across the 17 of their papers we have counts for
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cs.NE2019★ 296 cited
The Heidelberg spiking datasets for the systematic evaluation of spiking neural networks
Benjamin Cramer, Yannik Stradmann, Johannes Schemmel +1
Spiking neural networks are the basis of versatile and power-efficient information processing in the brain. Although we currently lack a detailed understanding of how these network…
cs.NE2019★ 149 cited
Surrogate Gradient Learning in Spiking Neural Networks
Emre O. Neftci, Hesham Mostafa, Friedemann Zenke
Spiking neural networks are nature's versatile solution to fault-tolerant and energy efficient signal processing. To translate these benefits into hardware, a growing number of neu…