7 citations · 15 across the 13 of their papers we have counts for
5 papers · 1 filter
Context Gating in Spiking Neural Networks: Achieving Lifelong Learning through Integration of Local and Global Plasticity
Jiangrong Shen, Wenyao Ni, Qi Xu +2
Humans learn multiple tasks in succession with minimal mutual interference, through the context gating mechanism in the prefrontal cortex (PFC). The brain-inspired models of spikin…
Enhancing Adaptive History Reserving by Spiking Convolutional Block Attention Module in Recurrent Neural Networks
Qi Xu, Yuyuan Gao, Jiangrong Shen +4
Spiking neural networks (SNNs) serve as one type of efficient model to process spatio-temporal patterns in time series, such as the Address-Event Representation data collected from…
Darwin3: A large-scale neuromorphic chip with a Novel ISA and On-Chip Learning
De Ma, Xiaofei Jin, Shichun Sun +8
Spiking Neural Networks (SNNs) are gaining increasing attention for their biological plausibility and potential for improved computational efficiency. To match the high spatial-tem…
Mitigating Communication Costs in Neural Networks: The Role of Dendritic Nonlinearity
Xundong Wu, Pengfei Zhao, Zilin Yu +6
Our understanding of biological neuronal networks has profoundly influenced the development of artificial neural networks (ANNs). However, neurons utilized in ANNs differ considera…
SPAIC: A Spike-based Artificial Intelligence Computing Framework
Chaofei Hong, Mengwen Yuan, Mengxiao Zhang +6
Neuromorphic computing is an emerging research field that aims to develop new intelligent systems by integrating theories and technologies from multi-disciplines such as neuroscien…