SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases Y Liu, J Cheng, H Zhao, T Xu, P Zhao, F Tsung, J Li, Y Rong The Twelfth International Conference on Learning Representations, 0 | 12* | |
All in one and one for all: A simple yet effective method towards cross-domain graph pretraining H Zhao, A Chen, X Sun, H Cheng, J Li Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 11 | 2024 |
A clothes classification method based on the gcforest L Han, Z Haihong, Y Erxin, B Yuming, L Huiying 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC …, 2018 | 10 | 2018 |
Effective fault scenario identification for communication networks via knowledge-enhanced graph neural networks H Zhao, B Yang, J Cui, Q Xing, J Shen, F Zhu, J Cao IEEE Transactions on Mobile Computing 23 (4), 3243-3258, 2023 | 9 | 2023 |
A dual-system method for intelligent fault localization in communication networks J Ji, F Zhu, J Cui, H Zhao, B Yang ICC 2022-IEEE International Conference on Communications, 4062-4067, 2022 | 5 | 2022 |
Weakly Supervised Anomaly Detection via Knowledge-Data Alignment H Zhao, C Zi, Y Liu, C Zhang, Y Zhou, J Li Proceedings of the ACM on Web Conference 2024, 4083–4094, 2024 | 4 | 2024 |
ProG: A Graph Prompt Learning Benchmark C Zi, H Zhao, X Sun, Y Lin, H Cheng, J Li arXiv preprint arXiv:2406.05346, 2024 | 1 | 2024 |