46 citations · 127 across the 13 of their papers we have counts for
30 papers
Attention Spiking Neural Networks
Man Yao, Guangshe Zhao, Hengyu Zhang +5
Benefiting from the event-driven and sparse spiking characteristics of the brain, spiking neural networks (SNNs) are becoming an energy-efficient alternative to artificial neural n…
Advancing Deep Residual Learning by Solving the Crux of Degradation in Spiking Neural Networks
Yifan Hu, Yujie Wu, Lei Deng +1
Despite the rapid progress of neuromorphic computing, the inadequate depth and the resulting insufficient representation power of spiking neural networks (SNNs) severely restrict t…
Survey on Graph Neural Network Acceleration: An Algorithmic Perspective
Xin Liu, Mingyu Yan, Lei Deng +5
Graph neural networks (GNNs) have been a hot spot of recent research and are widely utilized in diverse applications. However, with the use of huger data and deeper models, an urge…
H2Learn: High-Efficiency Learning Accelerator for High-Accuracy Spiking Neural Networks
Ling Liang, Zheng Qu, Zhaodong Chen +6
Although spiking neural networks (SNNs) take benefits from the bio-plausible neural modeling, the low accuracy under the common local synaptic plasticity learning rules limits thei…
Temporal-wise Attention Spiking Neural Networks for Event Streams Classification
Man Yao, Huanhuan Gao, Guangshe Zhao +4
How to effectively and efficiently deal with spatio-temporal event streams, where the events are generally sparse and non-uniform and have the microsecond temporal resolution, is o…
Exploiting Spiking Dynamics with Spatial-temporal Feature Normalization in Graph Learning
Mingkun Xu, Yujie Wu, Lei Deng +3
Biological spiking neurons with intrinsic dynamics underlie the powerful representation and learning capabilities of the brain for processing multimodal information in complex envi…