| 2025 | CVPR | USP-Gaussian: Unifying Spike-based Image Reconstruction, Pose Correction and Gaussian Splatting. | Kang Chen, Jiyuan Zhang, Zecheng Hao, Yajing Zheng, Tiejun Huang, Zhaofei Yu |
| 2025 | ICML | Faster and Stronger: When ANN-SNN Conversion Meets Parallel Spiking Calculation. | Zecheng Hao, Qichao Ma, Kang Chen, Yi Zhang, Zhaofei Yu, Tiejun Huang |
| 2025 | ICML | Differential Coding for Training-Free ANN-to-SNN Conversion. | Zihan Huang, Wei Fang, Tong Bu, Peng Xue, Zecheng Hao, Wenxuan Liu, Yuanhong Tang, Zhaofei Yu, Tiejun Huang |
| 2024 | CVPR | SpikingResformer: Bridging ResNet and Vision Transformer in Spiking Neural Networks. | Xinyu Shi, Zecheng Hao, Zhaofei Yu |
| 2024 | ICLR | Threaten Spiking Neural Networks through Combining Rate and Temporal Information. | Zecheng Hao, Tong Bu, Xinyu Shi, Zihan Huang, Zhaofei Yu, Tiejun Huang |
| 2024 | ICLR | A Progressive Training Framework for Spiking Neural Networks with Learnable Multi-hierarchical Model. | Zecheng Hao, Xinyu Shi, Zihan Huang, Tong Bu, Zhaofei Yu, Tiejun Huang |
| 2024 | ICLR | Towards Energy Efficient Spiking Neural Networks: An Unstructured Pruning Framework. | Xinyu Shi, Jianhao Ding, Zecheng Hao, Zhaofei Yu |
| 2024 | ICML | Enhancing Adversarial Robustness in SNNs with Sparse Gradients. | Yujia Liu, Tong Bu, Jianhao Ding, Zecheng Hao, Tiejun Huang, Zhaofei Yu |
| 2023 | AAAI | Reducing ANN-SNN Conversion Error through Residual Membrane Potential. | Zecheng Hao, Tong Bu, Jianhao Ding, Tiejun Huang, Zhaofei Yu |
| 2023 | CVPR | Rate Gradient Approximation Attack Threats Deep Spiking Neural Networks. | Tong Bu, Jianhao Ding, Zecheng Hao, Zhaofei Yu |
| 2023 | ICLR | Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes. | Zecheng Hao, Jianhao Ding, Tong Bu, Tiejun Huang, Zhaofei Yu |