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SSEL:基于尖峰的结构性热学习用于尖峰图形神经网络

Shuangming Yang1, Yuzhu Wu1, Badong Chen2

  • 1School of Electrical Automation and Information Engineering, Tianjin University, Tianjin, China.

Frontiers in neuroscience
|December 15, 2025
PubMed
概括

本研究介绍了基于尖端的结构学 (SSEL) 用于尖端图形神经网络 (SGNNs),增强对拓攻击的稳定性并降低能源消耗. 对于精细的图形来说,SSEL最大限度地降低了结构,提高了对抗防御和效率.

关键词:
大脑启发的智能是大脑启发的智能图形神经网络的神经网络神经形态计算的神经形态计算尖的神经网络的神经网络.结构的结构.

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