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20202023
most citedDeep Residual Learning in Spiking Neural Networks

224 citations · 301 across the 8 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.NE2023★ 3 cited

SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence

Wei Fang, Yanqi Chen, Jianhao Ding +7

Spiking neural networks (SNNs) aim to realize brain-inspired intelligence on neuromorphic chips with high energy efficiency by introducing neural dynamics and spike properties. As…

cs.NE2023

Auto-Spikformer: Spikformer Architecture Search

Kaiwei Che, Zhaokun Zhou, Zhengyu Ma +5

The integration of self-attention mechanisms into Spiking Neural Networks (SNNs) has garnered considerable interest in the realm of advanced deep learning, primarily due to their b…

cs.CV2023

Temporal Contrastive Learning for Spiking Neural Networks

Haonan Qiu, Zeyin Song, Yanqi Chen +6

Biologically inspired spiking neural networks (SNNs) have garnered considerable attention due to their low-energy consumption and spatio-temporal information processing capabilitie…

cs.NE2023★ 15 cited

Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-term Dependencies

Wei Fang, Zhaofei Yu, Zhaokun Zhou +5

Vanilla spiking neurons in Spiking Neural Networks (SNNs) use charge-fire-reset neuronal dynamics, which can only be simulated serially and can hardly learn long-time dependencies.…

cs.LG2023★ 6 cited

A Unified Framework for Soft Threshold Pruning

Yanqi Chen, Zhengyu Ma, Wei Fang +3

Soft threshold pruning is among the cutting-edge pruning methods with state-of-the-art performance. However, previous methods either perform aimless searching on the threshold sche…