2 citations · 3 across the 4 of their papers we have counts for
4 papers
CaRe-BN: Precise Moving Statistics for Stabilizing Spiking Neural Networks in Reinforcement Learning
Zijie Xu, Xinyu Shi, Yiting Dong +2
Spiking Neural Networks (SNNs) offer low-latency and energy-efficient decision-making on neuromorphic hardware by mimicking the event-driven dynamics of biological neurons. However…
Towards High-performance Spiking Transformers from ANN to SNN Conversion
Zihan Huang, Xinyu Shi, Zecheng Hao +4
Spiking neural networks (SNNs) show great potential due to their energy efficiency, fast processing capabilities, and robustness. There are two main approaches to constructing SNNs…
SpikingResformer: Bridging ResNet and Vision Transformer in Spiking Neural Networks
Xinyu Shi, Zecheng Hao, Zhaofei Yu
The remarkable success of Vision Transformers in Artificial Neural Networks (ANNs) has led to a growing interest in incorporating the self-attention mechanism and transformer-based…
LM-HT SNN: Enhancing the Performance of SNN to ANN Counterpart through Learnable Multi-hierarchical Threshold Model
Zecheng Hao, Xinyu Shi, Yujia Liu +2
Compared to traditional Artificial Neural Network (ANN), Spiking Neural Network (SNN) has garnered widespread academic interest for its intrinsic ability to transmit information in…