2 code implementations • 25 Mar 2024 • Chenlin Zhou, Han Zhang, Zhaokun Zhou, Liutao Yu, Liwei Huang, Xiaopeng Fan, Li Yuan, Zhengyu Ma, Huihui Zhou, Yonghong Tian
ii) We incorporate the hierarchical structure, which significantly benefits the performance of both the brain and artificial neural networks, into spiking transformers to obtain multi-scale spiking representation.
1 code implementation • 10 May 2023 • Chenlin Zhou, Han Zhang, Zhaokun Zhou, Liutao Yu, Zhengyu Ma, Huihui Zhou, Xiaopeng Fan, Yonghong Tian
In this paper, we propose ConvBN-MaxPooling-LIF (CML), an SNN-optimized downsampling with precise gradient backpropagation.
1 code implementation • 24 Apr 2023 • Chenlin Zhou, Liutao Yu, Zhaokun Zhou, Zhengyu Ma, Han Zhang, Huihui Zhou, Yonghong Tian
Based on this residual design, we develop Spikingformer, a pure transformer-based spiking neural network.
1 code implementation • 9 Mar 2023 • Liwei Huang, Zhengyu Ma, Liutao Yu, Huihui Zhou, Yonghong Tian
However, they highly simplify the computational properties of neurons compared to their biological counterparts.