Preprint
Oct 2026
SpikeQ: Spike-Guided Post-Training Quantization for Spiking Neural Networks
On neuromorphic chips, spiking neural networks (SNNs) consume far less energy than artificial neural networks (ANNs), but the limited memory of these chips requires low-bit synaptic weights and membrane potentials. Existing post-training quantization (PTQ) methods provide them without retraining and, like those for ANN...
Kai Sun, Pei-Bo Duan, Zhang-Lu Yan et al.
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