| 2026 | AAAI | Generalized Threshold Optimization with Harmony Multi-Threshold Neurons for Accurate ANN-to-SNN Conversion. | Wenhan Zhang, Zihan Huang, Tong Bu, Tiejun Huang, Zhaofei Yu |
| 2025 | CVPR | Inference-Scale Complexity in ANN-SNN Conversion for High-Performance and Low-Power Applications. | Tong Bu, Maohua Li, Zhaofei Yu |
| 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 | 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 | 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 |
| 2022 | AAAI | Optimized Potential Initialization for Low-Latency Spiking Neural Networks. | Tong Bu, Jianhao Ding, Zhaofei Yu, Tiejun Huang |
| 2022 | ICLR | Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks. | Tong Bu, Wei Fang, Jianhao Ding, Penglin Dai, Zhaofei Yu, Tiejun Huang |