4 papers
MPD-SGR: Robust Spiking Neural Networks with Membrane Potential Distribution-Driven Surrogate Gradient Regularization
Runhao Jiang, Chengzhi Jiang, Rui Yan +1
The surrogate gradient (SG) method has shown significant promise in enhancing the performance of deep spiking neural networks (SNNs), but it also introduces vulnerabilities to adve…
Adaptive Gradient Learning for Spiking Neural Networks by Exploiting Membrane Potential Dynamics
Jiaqiang Jiang, Lei Wang, Runhao Jiang +2
Brain-inspired spiking neural networks (SNNs) are recognized as a promising avenue for achieving efficient, low-energy neuromorphic computing. Recent advancements have focused on d…
ASRC-SNN: Adaptive Skip Recurrent Connection Spiking Neural Network
Shang Xu, Jiayu Zhang, Ziming Wang +3
In recent years, Recurrent Spiking Neural Networks (RSNNs) have shown promising potential in long-term temporal modeling. Many studies focus on improving neuron models and also int…
Enhancing SNN-based Spatio-Temporal Learning: A Benchmark Dataset and Cross-Modality Attention Model
Shibo Zhou, Bo Yang, Mengwen Yuan +4
Spiking Neural Networks (SNNs), renowned for their low power consumption, brain-inspired architecture, and spatio-temporal representation capabilities, have garnered considerable a…