Gu, Shi

13 publications

CVPR 2025 Hybrid Concept Bottleneck Models Yang Liu, Tianwei Zhang, Shi Gu

NeurIPS 2025 Rethinking Hebbian Principle: Low-Dimensional Structural Projection for Unsupervised Learning Shikuang Deng, Jiayuan Zhang, Yuhang Wu, Ting Chen, Shi Gu

ICLR 2025 Temporal Flexibility in Spiking Neural Networks: Towards Generalization Across Time Steps and Deployment Friendliness Kangrui Du, Yuhang Wu, Shikuang Deng, Shi Gu

NeurIPS 2024 Spiking Token Mixer: An Event-Driven Friendly Former Structure for Spiking Neural Networks Shikuang Deng, Yuhang Wu, Kangrui Du, Shi Gu

MIDL 2024 Train Once, Deploy Anywhere: Edge-Guided Single-Source Domain Generalization for Medical Image Segmentation Jun Jiang, Shi Gu

ICMLW 2023 Efficient Surrogate Gradients for Training Spiking Neural Networks Hao Lin, Shikuang Deng, Shi Gu

ICML 2023 Surrogate Module Learning: Reduce the Gradient Error Accumulation in Training Spiking Neural Networks Shikuang Deng, Hao Lin, Yuhang Li, Shi Gu

ICLR 2022 Temporal Efficient Training of Spiking Neural Network via Gradient Re-Weighting Shikuang Deng, Yuhang Li, Shanghang Zhang, Shi Gu

ICML 2021 A Free Lunch from ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration Yuhang Li, Shikuang Deng, Xin Dong, Ruihao Gong, Shi Gu

ICLR 2021 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

NeurIPS 2021 Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks Yuhang Li, Yufei Guo, Shanghang Zhang, Shikuang Deng, Yongqing Hai, Shi Gu

ICCV 2021 MixMix: All You Need for Data-Free Compression Are Feature and Data Mixing Yuhang Li, Feng Zhu, Ruihao Gong, Mingzhu Shen, Xin Dong, Fengwei Yu, Shaoqing Lu, Shi Gu

ICLR 2021 Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks Shikuang Deng, Shi Gu