Publications
Please see Google Scholar
2025
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A concept-based interpretable model for the diagnosis of choroid neoplasias using multimodal data
Yifan Wu, Yang Liu, Yue Yang, Michael S Yao, Wenli Yang, Xuehui Shi, Lihong Yang, Dongjun Li, Yueming Liu, Shiyi Yin, Chunyan Lei, Meixia Zhang, James C Gee, Xuan Yang, Wenbin Wei, Shi Gu
Nature Communications 16, no. 1 (2025): 3504.
[Paper] [Project]
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A Temporal Flexibility in Spiking Neural Networks: Towards Generalization Across Time Steps and Deployment Friendliness
Kangrui Du, Yuhang Wu, Shikuang Deng, Shi Gu
The Thirteenth International Conference on Learning Representations.
[Paper] [Project]
2024
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Emergence and reconfiguration of modular structure for artificial neural networks during continual familiarity detection
Shi Gu, Marcelo G Mattar, Huajin Tang, Gang Pan
Science Advances 10, no. 30 (2024): eadm8430.
[Paper] [Project]
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Spiking Token Mixer: An event-driven friendly Former structure for spiking neural networks
Shikuang Deng, Yuhang Wu, Kangrui Du, Shi Gu
The Thirty-eighth Annual Conference on Neural Information Processing Systems.
[Paper] [Project]
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Enhancing neural encoding models for naturalistic perception with a multi-level integration of deep neural networks and cortical networks
Yuanning Li, Huzheng Yang, Shi Gu
Science Bulletin 69, no. 11 (2024): 1738-1747.
[Paper] [Project]
2023
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Surrogate module learning: Reduce the gradient error accumulation in training spiking neural networks
Shikuang Deng, Hao Lin, Yuhang Li, Shi Gu
International Conference on Machine Learning, pp. 7645-7657. PMLR, 2023.
[Paper] [Project]
2021-2022
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Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting
Shikuang Deng, Yuhang Li, Shanghang Zhang, Shi Gu
International Conference on Learning Representations (ICLR) 2022.
[Paper] [Project] [Citation > 350]
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Differentiable spike: Rethinking gradient-descent for training spiking neural networks
Yuhang Li, Yufei Guo, Shanghang Zhang, Shikuang Deng, Yongqing Hai, Shi Gu
Proceedings of the 35th International Conference on Neural Information Processing Systems, pp. 23426-23439. 2021.
[Paper] [Project] [Citation > 300]
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Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks
Shikuang Deng, Shi Gu
International Conference on Learning Representations (ICLR) 2021.
[Paper] [Project] [Citation > 250]
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Brecq: Pushing the limit of post-training quantization by block reconstruction
Yuhang Li, Ruihao Gong, Xu Tan, Yang Yang, Peng Hu, Qi Zhang, Fengwei Yu, Wei Wang, Shi Gu
International Conference on Learning Representations (ICLR) 2021.
[Paper] [Project] [Citation > 550]