A signed quantized activation plus a multi-spike signed neuron makes a one-timestep spiking network reproduce the quantized ANN exactly, giving ANN-identical accuracy at T=1 on CIFAR-10/100 and state-of-the-art one-step accuracy on ImageNet and event datasets.
Optimal ANN-SNN conversion for fast and accurate inference in deep spiking neural networks,
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Quantization Meets Spikes: Nearly Lossless Conversion at the First Timestep via Polarity Multi-Spike Mapping
A signed quantized activation plus a multi-spike signed neuron makes a one-timestep spiking network reproduce the quantized ANN exactly, giving ANN-identical accuracy at T=1 on CIFAR-10/100 and state-of-the-art one-step accuracy on ImageNet and event datasets.