2 citations · 3 across the 6 of their papers we have counts for
7 papers
Neural Dynamics Self-Attention for Spiking Transformers
Dehao Zhang, Fukai Guo, Shuai Wang +6
Integrating Spiking Neural Networks (SNNs) with Transformer architectures offers a promising pathway to balance energy efficiency and performance, particularly for edge vision appl…
Unveiling the Spatial-temporal Effective Receptive Fields of Spiking Neural Networks
Jieyuan Zhang, Xiaolong Zhou, Shuai Wang +6
Spiking Neural Networks (SNNs) demonstrate significant potential for energy-efficient neuromorphic computing through an event-driven paradigm. While training methods and computatio…
SNN: Sub-bit Spiking Neural Networks
Wenjie Wei, Malu Zhang, Jieyuan Zhang +8
Spiking Neural Networks (SNNs) offer an energy-efficient paradigm for machine intelligence, but their continued scaling poses challenges for resource-limited deployment. Despite re…
Training-Free ANN-to-SNN Conversion for High-Performance Spiking Transformer
Jingya Wang, Xin Deng, Wenjie Wei +7
Leveraging the event-driven paradigm, Spiking Neural Networks (SNNs) offer a promising approach for energy-efficient Transformer architectures.While ANN-to-SNN conversion avoids th…
SDTrack: A Baseline for Event-based Tracking via Spiking Neural Networks
Yimeng Shan, Zhenbang Ren, Haodi Wu +11
Event cameras provide superior temporal resolution, dynamic range, energy efficiency, and pixel bandwidth. Spiking Neural Networks (SNNs) naturally complement event data through di…
QP-SNN: Quantized and Pruned Spiking Neural Networks
Wenjie Wei, Malu Zhang, Zijian Zhou +6
Brain-inspired Spiking Neural Networks (SNNs) leverage sparse spikes to encode information and operate in an asynchronous event-driven manner, offering a highly energy-efficient pa…