1 citations · 1 across the 3 of their papers we have counts for
10 papers
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…
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…
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…
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…