105 citations · 217 across the 26 of their papers we have counts for
7 papers · 1 filter
Spike-driven Transformer
Man Yao, Jiakui Hu, Zhaokun Zhou +4
Spiking Neural Networks (SNNs) provide an energy-efficient deep learning option due to their unique spike-based event-driven (i.e., spike-driven) paradigm. In this paper, we incorp…
Long-Range Feedback Spiking Network Captures Dynamic and Static Representations of the Visual Cortex under Movie Stimuli
Liwei Huang, Zhengyu Ma, Liutao Yu +2
Deep neural networks (DNNs) are widely used models for investigating biological visual representations. However, existing DNNs are mostly designed to analyze neural responses to st…
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…
Enhancing the Performance of Transformer-based Spiking Neural Networks by SNN-optimized Downsampling with Precise Gradient Backpropagation
Chenlin Zhou, Han Zhang, Zhaokun Zhou +5
Deep spiking neural networks (SNNs) have drawn much attention in recent years because of their low power consumption, biological rationality and event-driven property. However, sta…
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.…
Training Full Spike Neural Networks via Auxiliary Accumulation Pathway
Guangyao Chen, Peixi Peng, Guoqi Li +1
Due to the binary spike signals making converting the traditional high-power multiply-accumulation (MAC) into a low-power accumulation (AC) available, the brain-inspired Spiking Ne…
Spikformer: When Spiking Neural Network Meets Transformer
Zhaokun Zhou, Yuesheng Zhu, Chao He +4
We consider two biologically plausible structures, the Spiking Neural Network (SNN) and the self-attention mechanism. The former offers an energy-efficient and event-driven paradig…