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cs.NE2020
Brain-Inspired Learning on Neuromorphic Substrates
Friedemann Zenke, Emre O. Neftci
Neuromorphic hardware strives to emulate brain-like neural networks and thus holds the promise for scalable, low-power information processing on temporal data streams. Yet, to solv…
cs.LG2020★ 4 cited
Finding trainable sparse networks through Neural Tangent Transfer
Tianlin Liu, Friedemann Zenke
Deep neural networks have dramatically transformed machine learning, but their memory and energy demands are substantial. The requirements of real biological neural networks are ra…