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Yang Li1, Feifei Zhao1, Dongcheng Zhao2

  • 1Brain-inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences (CAS), Beijing, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China.

概括

这项研究引入了蒙面替代梯度 (MSG) 和时间加权输出 (TWO),以改善尖端神经网络 (SNN) 训练. 这些方法通过平衡训练有效性和梯度稀疏性来提高SNN的性能.