12 citations · 13 across the 4 of their papers we have counts for
6 papers
Parallel Time-Aligned Spiking Self-Attention for Consistent Integer-Valued Training and Spike-Driven Inference
Peng Xue, Wei Fang, Kaiwei Che +4
Integer-valued leaky integrate-and-fire (I-LIF) neurons and spike firing approximation (SFA) reduce temporal training cost by representing spike trains as firing counts and normali…
Multiplication-Free Parallelizable Spiking Neurons with Efficient Spatio-Temporal Dynamics
Peng Xue, Wei Fang, Zhengyu Ma +5
Spiking Neural Networks (SNNs) are distinguished from Artificial Neural Networks (ANNs) for their complex neuronal dynamics and sparse binary activations (spikes) inspired by the b…
Scalable Dendritic Modeling Advances Expressive and Robust Deep Spiking Neural Networks
Yifan Huang, Wei Fang, Zhengyu Ma +2
Dendritic computation endows biological neurons with rich nonlinear integration and high representational capacity, yet it is largely missing in existing deep spiking neural networ…
Efficiently Training Time-to-First-Spike Spiking Neural Networks from Scratch
Kaiwei Che, Zhengyu Ma, Yifan Huang +5
Spiking Neural Networks (SNNs), with their event-driven and biologically inspired mechanisms, are well-suited for energy-efficient neuromorphic hardware. Neural coding, which is cr…
Optimal ANN-SNN Conversion with Group Neurons
Liuzhenghao Lv, Wei Fang, Li Yuan +1
Spiking Neural Networks (SNNs) have emerged as a promising third generation of neural networks, offering unique characteristics such as binary outputs, high sparsity, and biologica…
Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN Ticket
Zhaokun Zhou, Yijie Lu, Kaiwei Che +7
Spiking Neural Networks (SNNs), known for their biologically plausible architecture, face the challenge of limited performance. The self-attention mechanism, which is the cornersto…