| 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 | 296* | 2023 |
| 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 | 242 | 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 | 168 | 2021 |
| 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 | 101 | 2022 |
| 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 | 95 | 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 | 58 | 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 | 43 | 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 | 32 | 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 | 18 | 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 | 14 | 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 | 8 | 2023 |
| Online stabilization of spiking neural networks Y Zhu, J Ding, T Huang, X Xie, Z Yu The Twelfth International Conference on Learning Representations, 2024 | 7 | 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 | 6 | 2024 |
| Defense Against Adversarial Attacks on No-Reference Image Quality Models with Gradient Norm Regularization Y Liu, C Yang, D Li, J Ding, T Jiang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 5 | 2024 |
| 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 |
| Towards High-performance Spiking Transformers from ANN to SNN Conversion Z Huang, X Shi, Z Hao, T Bu, J Ding, Z Yu, T Huang Proceedings of the 32nd ACM International Conference on Multimedia, 10688-10697, 2024 | 2 | 2024 |
| Accelerating training of deep spiking neural networks with parameter initialization J Ding, J Zhang, Z Yu, T Huang | 2 | 2022 |
| Towards human-leveled vision systems J Ding, T Huang SCIENCE CHINA Technological Sciences, 2024 | 1 | 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 | 1 | 2024 |
| Robust Stable Spiking Neural Networks J Ding, Z Pan, Y Liu, Z Yu, T Huang The Forty-first International Conference on Machine Learning, 2024 | 1 | 2024 |
Zhaofei YuPeking Universitypku.edu.cn의 이메일 확인됨