1 citations · 2 across the 12 of their papers we have counts for
8 papers · 1 filter
BSO: Binary Spiking Online Optimization Algorithm
Yu Liang, Yu Yang, Wenjie Wei +4
Binary Spiking Neural Networks (BSNNs) offer promising efficiency advantages for resource-constrained computing. However, their training algorithms often require substantial memory…
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…
Dendritic Resonate-and-Fire Neuron for Effective and Efficient Long Sequence Modeling
Dehao Zhang, Malu Zhang, Shuai Wang +6
The explosive growth in sequence length has intensified the demand for effective and efficient long sequence modeling. Benefiting from intrinsic oscillatory membrane dynamics, Reso…
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…
Memory-Free and Parallel Computation for Quantized Spiking Neural Networks
Dehao Zhang, Shuai Wang, Yichen Xiao +4
Quantized Spiking Neural Networks (QSNNs) offer superior energy efficiency and are well-suited for deployment on resource-limited edge devices. However, limited bit-width weight an…
Towards Accurate Binary Spiking Neural Networks: Learning with Adaptive Gradient Modulation Mechanism
Yu Liang, Wenjie Wei, Ammar Belatreche +5
Binary Spiking Neural Networks (BSNNs) inherit the eventdriven paradigm of SNNs, while also adopting the reduced storage burden of binarization techniques. These distinct advantage…
Spiking Vision Transformer with Saccadic Attention
Shuai Wang, Malu Zhang, Dehao Zhang +7
The combination of Spiking Neural Networks (SNNs) and Vision Transformers (ViTs) holds potential for achieving both energy efficiency and high performance, particularly suitable fo…
Binary Event-Driven Spiking Transformer
Honglin Cao, Zijian Zhou, Wenjie Wei +6
Transformer-based Spiking Neural Networks (SNNs) introduce a novel event-driven self-attention paradigm that combines the high performance of Transformers with the energy efficienc…