| Spiking graph convolutional networks Z Zhu, J Peng, J Li, L Chen, Q Yu, S Luo arXiv preprint arXiv:2205.02767, 2022 | 42 | 2022 |
| Loop detection and correction of 3d laser-based slam with visual information Z Zhu, S Yang, H Dai, F Li Proceedings of the 31st International Conference on Computer Animation and …, 2018 | 26 | 2018 |
| Scaling up dynamic graph representation learning via spiking neural networks J Li, Z Yu, Z Zhu, L Chen, Q Yu, Z Zheng, S Tian, R Wu, C Meng Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 8588-8596, 2023 | 20 | 2023 |
| A graph is worth 1-bit spikes: When graph contrastive learning meets spiking neural networks J Li, H Zhang, R Wu, Z Zhu, B Wang, C Meng, Z Zheng, L Chen arXiv preprint arXiv:2305.19306, 2023 | 5 | 2023 |
| Fastgcl: Fast self-supervised learning on graphs via contrastive neighborhood aggregation Y Wang, W Sun, K Xu, Z Zhu, L Chen, Z Zheng arXiv preprint arXiv:2205.00905, 2022 | 5 | 2022 |
| Enhanced visual loop closing for laser-based SLAM Z Zhu, S Yang, H Dai 2018 IEEE 29th international conference on application-specific systems …, 2018 | 5 | 2018 |
| Personalized PageRanks over Dynamic Graphs–The Case for Optimizing Quality of Service Z Zhu, S Wang, S Luo, D Mo, W Lin, C Li Proceedings of the 2024 IEEE 40th International Conference on Data Engineering, 2024 | 3 | 2024 |
| Massively Parallel Single-Source SimRanks in Rounds S Luo, Z Zhu arXiv preprint arXiv:2304.04015, 2023 | 1 | 2023 |
| Benchmarking Spectral Graph Neural Networks: A Comprehensive Study on Effectiveness and Efficiency N Liao, H Liu, Z Zhu, S Luo, LVS Lakshmanan arXiv preprint arXiv:2406.09675, 2024 | | 2024 |
| Topology-monitorable Contrastive Learning on Dynamic Graphs Z Zhu, K Wang, H Liu, J Li, S Luo | | 2024 |
