Reducing ANN-SNN Conversion Error through Residual Membrane Potential. - Zecheng Hao; Tong Bu; Jianhao Ding; Tiejun Huang 001; Zhaofei Yu (AAAI, 2023)

Rate Gradient Approximation Attack Threats Deep Spiking Neural Networks. - Tong Bu; Jianhao Ding; Zecheng Hao; Zhaofei Yu (CVPR, 2023)

Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes. - Zecheng Hao; Jianhao Ding; Tong Bu; Tiejun Huang 001; Zhaofei Yu (ICLR, 2023)

SpikingResformer: Bridging ResNet and Vision Transformer in Spiking Neural Networks. - Xinyu Shi; Zecheng Hao; Zhaofei Yu (CVPR, 2024)

Threaten Spiking Neural Networks through Combining Rate and Temporal Information. - Zecheng Hao; Tong Bu; Xinyu Shi; Zihan Huang; Zhaofei Yu; Tiejun Huang 001 (ICLR, 2024)

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 001 (ICLR, 2024)

Towards Energy Efficient Spiking Neural Networks: An Unstructured Pruning Framework. - Xinyu Shi; Jianhao Ding; Zecheng Hao; Zhaofei Yu (ICLR, 2024)

Enhancing Adversarial Robustness in SNNs with Sparse Gradients. - Yujia Liu 005; Tong Bu; Jianhao Ding; Zecheng Hao; Tiejun Huang 001; Zhaofei Yu (ICML, 2024)

Towards High-performance Spiking Transformers from ANN to SNN Conversion. - Zihan Huang; Xinyu Shi; Zecheng Hao; Tong Bu; Jianhao Ding; Zhaofei Yu; Tiejun Huang 001 (ACM Multimedia, 2024)

Take A Shortcut Back: Mitigating the Gradient Vanishing for Training Spiking Neural Networks. - Yufei Guo; Yuanpei Chen; Zecheng Hao; Weihang Peng 001; Zhou Jie; Yuhan Zhang; Xiaode Liu; Zhe Ma 001 (NeurIPS, 2024)

LM-HT SNN: Enhancing the Performance of SNN to ANN Counterpart through Learnable Multi-hierarchical Threshold Model. - Zecheng Hao; Xinyu Shi; Yujia Liu 005; Zhaofei Yu; Tiejun Huang 001 (NeurIPS, 2024)

LM-HT SNN: Enhancing the Performance of SNN to ANN Counterpart through Learnable Multi-hierarchical Threshold Model. - Zecheng Hao; Xinyu Shi; Zhiyu Pan; Yujia Liu 005; Zhaofei Yu; Tiejun Huang 001 (CoRR, 2024)

UP-Diff: Latent Diffusion Model for Remote Sensing Urban Prediction. - Zeyu Wang; Zecheng Hao; Jingyu Lin; Yuchao Feng; Yufei Guo (CoRR, 2024)

Comprehensive Online Training and Deployment for Spiking Neural Networks. - Zecheng Hao; Yifan Huang 002; Zijie Xu 008; Zhaofei Yu; Tiejun Huang 001 (CoRR, 2024)

Faster and Stronger: When ANN-SNN Conversion Meets Parallel Spiking Calculation. - Zecheng Hao; Zhaofei Yu; Tiejun Huang 001 (CoRR, 2024)

USP-Gaussian: Unifying Spike-based Image Reconstruction, Pose Correction and Gaussian Splatting. - Kang Chen; Jiyuan Zhang; Zecheng Hao; Yajing Zheng; Tiejun Huang 001; Zhaofei Yu (CVPR, 2025)

UP-Diff: Latent Diffusion Model for Remote Sensing Urban Prediction. - Zeyu Wang 010; Zecheng Hao; Yuhan Zhang; Yuchao Feng; Yufei Guo (IEEE Geosci. Remote. Sens. Lett., 2025)

PT-BitNet: Scaling up the 1-Bit large language model with post-training quantization. - Yufei Guo; Zecheng Hao; Jiahang Shao; Jie Zhou; Xiaode Liu; Xin Tong; Yuhan Zhang; Yuanpei Chen; Weihang Peng 001; Zhe Ma 001 (Neural Networks, 2025)

Differential Coding for Training-Free ANN-to-SNN Conversion. - Zihan Huang; Wei Fang 006; Tong Bu; Peng Xue; Zecheng Hao; Wenxuan Liu; Yuanhong Tang; Zhaofei Yu; Tiejun Huang 001 (CoRR, 2025)

Proxy Target: Bridging the Gap Between Discrete Spiking Neural Networks and Continuous Control. - Zijie Xu 008; Tong Bu; Zecheng Hao; Jianhao Ding; Zhaofei Yu (CoRR, 2025)