5 papers
ELSA: An ELastic SNN Inference Architecture for Efficient Neuromorphic Computing
Kang You, Chen Nie, Lee Jun Yan +6
Spiking neural networks (SNNs) exploit event-driven and addition-only computation to substantially improve efficiency for intelligent computation. A key temporal property of SNNs,…
Determinism in the Undetermined: Deterministic Output in Charge-Conserving Continuous-Time Neuromorphic Systems with Temporal Stochasticity
Jing Yan, Kang You, Zhezhi He +1
Achieving deterministic computation results in asynchronous neuromorphic systems remains a fundamental challenge due to the inherent temporal stochasticity of continuous-time hardw…
Obtaining Optimal Spiking Neural Network in Sequence Learning via CRNN-SNN Conversion
Jiahao Su, Kang You, Zekai Xu +2
Spiking neural networks (SNNs) are becoming a promising alternative to conventional artificial neural networks (ANNs) due to their rich neural dynamics and the implementation of en…
BKDSNN: Enhancing the Performance of Learning-based Spiking Neural Networks Training with Blurred Knowledge Distillation
Zekai Xu, Kang You, Qinghai Guo +2
Spiking neural networks (SNNs), which mimic biological neural system to convey information via discrete spikes, are well known as brain-inspired models with excellent computing eff…
SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN
Kang You, Zekai Xu, Chen Nie +4
Spiking neural network (SNN) has attracted great attention due to its characteristic of high efficiency and accuracy. Currently, the ANN-to-SNN conversion methods can obtain ANN on…