| Optimal ANN-SNN conversion for high-accuracy and ultra-low-latency spiking neural networks T Bu, W Fang, J Ding, PL Dai, Z Yu, T Huang arXiv preprint arXiv:2303.04347, 2023 | 193 | 2023 |
| Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networks J Ding, Z Yu, Y Tian, T Huang Proceedings of the Thirtieth International Joint Conference on Artificial …, 2021 | 144 | 2021 |
| Spikingjelly: An open-source machine learning infrastructure platform for spike-based intelligence W Fang, Y Chen, J Ding, Z Yu, T Masquelier, D Chen, L Huang, H Zhou, ... Science Advances 9 (40), eadi1480, 2023 | 117 | 2023 |
| Optimized potential initialization for low-latency spiking neural networks T Bu, J Ding, Z Yu, T Huang Proceedings of the AAAI conference on artificial intelligence 36 (1), 11-20, 2022 | 87 | 2022 |
| Spikingjelly W Fang, Y Chen, J Ding, D Chen, Z Yu, H Zhou, Y Tian Multimedia Learn. Group, Inst. Digit. Media (NELVT), 2020 | 84 | 2020 |
| Temporal effective batch normalization in spiking neural networks C Duan, J Ding, S Chen, Z Yu, T Huang Advances in Neural Information Processing Systems 35, 34377-34390, 2022 | 72 | 2022 |
| Reducing ann-snn conversion error through residual membrane potential Z Hao, T Bu, J Ding, T Huang, Z Yu Proceedings of the AAAI Conference on Artificial Intelligence 37 (1), 11-21, 2023 | 42 | 2023 |
| Bridging the gap between anns and snns by calibrating offset spikes Z Hao, J Ding, T Bu, T Huang, Z Yu arXiv preprint arXiv:2302.10685, 2023 | 35 | 2023 |
| SNN-RAT: Robustness-enhanced spiking neural network through regularized adversarial training J Ding, T Bu, Z Yu, T Huang, J Liu Advances in Neural Information Processing Systems 35, 24780-24793, 2022 | 27 | 2022 |
| Rate gradient approximation attack threats deep spiking neural networks T Bu, J Ding, Z Hao, Z Yu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 13 | 2023 |
| Towards energy efficient spiking neural networks: An unstructured pruning framework X Shi, J Ding, Z Hao, Z Yu The Twelfth International Conference on Learning Representations, 2024 | 8 | 2024 |
| Enhancing the robustness of spiking neural networks with stochastic gating mechanisms J Ding, Z Yu, T Huang, JK Liu Proceedings of the AAAI Conference on Artificial Intelligence 38 (1), 492-502, 2024 | 4 | 2024 |
| SpikeCV: Open a Continuous Computer Vision Era Y Zheng, J Zhang, R Zhao, J Ding, S Chen, R Xiong, Z Yu, T Huang arXiv preprint arXiv:2303.11684, 2023 | 4 | 2023 |
| An adaptive control momentum method as an optimizer in the cloud J Ding, L Han, D Li Future Generation Computer Systems 89, 192-200, 2018 | 3 | 2018 |
| Online stabilization of spiking neural networks Y Zhu, J Ding, T Huang, X Xie, Z Yu The Twelfth International Conference on Learning Representations, 2024 | 2 | 2024 |
| Accelerating training of deep spiking neural networks with parameter initialization J Ding, J Zhang, Z Yu, T Huang | 2 | 2022 |
| Towards High-performance Spiking Transformers from ANN to SNN Conversion Z Huang, X Shi, Z Hao, T Bu, J Ding, Z Yu, T Huang ACM Multimedia 2024, 2024 | 1 | 2024 |
| Towards human-leveled vision systems J Ding, T Huang SCIENCE CHINA Technological Sciences, 2024 | | 2024 |
| Enhancing Adversarial Robustness in SNNs with Sparse Gradients Y Liu, T Bu, J Ding, Z Hao, T Huang, Z Yu arXiv preprint arXiv:2405.20355, 2024 | | 2024 |
| Converting High-Performance and Low-Latency SNNs through Explicit Modelling of Residual Error in ANNs Z Huang, J Ding, Z Pan, H Li, Y Fang, Z Yu, JK Liu arXiv preprint arXiv:2404.17456, 2024 | | 2024 |
Zhaofei YuPeking UniversityVerified email at pku.edu.cn