| Invertible image rescaling M Xiao, S Zheng, C Liu, Y Wang, D He, G Ke, J Bian, Z Lin, TY Liu Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 278 | 2020 |
| Training high-performance low-latency spiking neural networks by differentiation on spike representation Q Meng, M Xiao, S Yan, Y Wang, Z Lin, ZQ Luo Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 164 | 2022 |
| Online Training Through Time for Spiking Neural Networks M Xiao, Q Meng, Z Zhang, D He, Z Lin Advances in Neural Information Processing Systems, 2022 | 83 | 2022 |
| Training feedback spiking neural networks by implicit differentiation on the equilibrium state M Xiao, Q Meng, Z Zhang, Y Wang, Z Lin Advances in neural information processing systems 34, 14516-14528, 2021 | 72 | 2021 |
| Towards Memory-and Time-Efficient Backpropagation for Training Spiking Neural Networks Q Meng, M Xiao, S Yan, Y Wang, Z Lin, ZQ Luo International Conference on Computer Vision, 2023 | 50 | 2023 |
| TDMPNet: Prototype Network with Recurrent Top-Down Modulation for Robust Object Classification Under Partial Occlusion M Xiao, A Kortylewski, R Wu, S Qiao, W Shen, A Yuille European Conference on Computer Vision Workshops, 447-463, 2020 | 37* | 2020 |
| Training much deeper spiking neural networks with a small number of time-steps Q Meng, S Yan, M Xiao, Y Wang, Z Lin, ZQ Luo Neural Networks 153, 254-268, 2022 | 33 | 2022 |
| Invertible rescaling network and its extensions M Xiao, S Zheng, C Liu, Z Lin, TY Liu International Journal of Computer Vision 131 (1), 134-159, 2023 | 29 | 2023 |
| Modeling lost information in lossy image compression Y Wang, M Xiao, C Liu, S Zheng, TY Liu arXiv preprint arXiv:2006.11999, 2020 | 27 | 2020 |
| Training neural networks by lifted proximal operator machines J Li, M Xiao, C Fang, Y Dai, C Xu, Z Lin IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (6), 3334-3348, 2020 | 23 | 2020 |
| SPIDE: A purely spike-based method for training feedback spiking neural networks M Xiao, Q Meng, Z Zhang, Y Wang, Z Lin Neural Networks 161, 9-24, 2023 | 13 | 2023 |
| Cross-patient automatic epileptic seizure detection using patient-adversarial neural networks with spatio-temporal EEG augmentation Z Zhang, T Ji, M Xiao, W Wang, G Yu, T Lin, Y Jiang, X Zhou, Z Lin Biomedical Signal Processing and Control 89, 105664, 2024 | 11 | 2024 |
| Efficient and generalizable cross-patient epileptic seizure detection through a spiking neural network Z Zhang, M Xiao, T Ji, Y Jiang, T Lin, X Zhou, Z Lin Frontiers in Neuroscience 17, 1303564, 2024 | 8 | 2024 |
| Sampling complex topology structures for spiking neural networks S Yan, Q Meng, M Xiao, Y Wang, Z Lin Neural Networks 172, 106121, 2024 | 6 | 2024 |
| Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks M Xiao, Q Meng, Z Zhang, D He, Z Lin International Conference on Learning Representations, 2024 | 4 | 2024 |
| Designing Universally-Approximating Deep Neural Networks: A First-Order Optimization Approach Z Wu, M Xiao, C Fang, Z Lin IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 3 | 2024 |
| Online Pseudo-Zeroth-Order Training of Neuromorphic Spiking Neural Networks M Xiao, Q Meng, Z Zhang, D He, Z Lin arXiv preprint arXiv:2407.12516, 2024 | 1 | 2024 |
| Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning M Xiao, Y Zhu, D He, Z Lin International Conference on Machine Learning, 2024 | | 2024 |
| Forward Gradient Training of Spiking Neural Networks M Xiao, Q Meng, Z Zhang, D He, Z Lin | | |
| Supplementary Materials for: Towards Memory-and Time-Efficient Backpropagation for Training Spiking Neural Networks Q Meng, M Xiao, S Yan, Y Wang, Z Lin, ZQ Luo | | |
Zhouchen LinProfessor, Peking University; Fellow of IEEE, IAPR, CSIG & AAIA; ex-VP of Samsung Researchpku.edu.cn의 이메일 확인됨
