| Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation Y Lu, Y Fang, C Shi Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 354 | 2020 |
| GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks Z Liu, X Yu, Y Fang, X Zhang Proceedings of the ACM Web Conference 2023, 417-428, 2023 | 316 | 2023 |
| Adversarial Learning on Heterogeneous Information Networks B Hu, Y Fang, C Shi ACM SIGKDD international conference on knowledge discovery and data mining (KDD), 2019 | 274 | 2019 |
| Graph Foundation Models: Concepts, Opportunities and Challenges J Liu, C Yang, Z Lu, J Chen, Y Li, M Zhang, T Bai, Y Fang, L Sun, PS Yu, ... IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025 | 194* | 2025 |
| Learning to pre-train graph neural networks Y Lu, X Jiang, Y Fang, C Shi Proceedings of the AAAI Conference on Artificial Intelligence 35 (5), 4276-4284, 2021 | 182 | 2021 |
| Tail-GNN: Tail-Node Graph Neural Networks Z Liu, TK Nguyen, Y Fang Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 173 | 2021 |
| Object Detection Meets Knowledge Graphs Y Fang, K Kuan, J Lin, C Tan, V Chandrasekhar International Joint Conference on Artificial Intelligence (IJCAI), 2017 | 154 | 2017 |
| Pre-training graph neural networks for link prediction in biomedical networks Y Long, M Wu, Y Liu, Y Fang, CK Kwoh, J Chen, J Luo, X Li Bioinformatics 38 (8), 2254-2262, 2022 | 128 | 2022 |
| Semantic Proximity Search on Graphs with Metagraph-based Learning Y Fang, W Lin, VW Zheng, M Wu, KCC Chang, X Li International Conference on Data Engineering (ICDE), 2016 | 127 | 2016 |
| TREND: TempoRal Event and Node Dynamics for Graph Representation Learning Z Wen, Y Fang Proceedings of the ACM Web Conference 2022, 1159-1169, 2022 | 122 | 2022 |
| Relative and absolute location embedding for few-shot node classification on graph Z Liu, Y Fang, C Liu, SCH Hoi Proceedings of the AAAI Conference on Artificial Intelligence 35 (5), 4267-4275, 2021 | 118 | 2021 |
| Augmenting low-resource text classification with graph-grounded pre-training and prompting Z Wen, Y Fang Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023 | 114 | 2023 |
| Dual-Dropout Graph Convolutional Network for Predicting Synthetic Lethality in Human Cancers R Cai, X Chen, Y Fang, M Wu, Y Hao Bioinformatics 36 (16), 4458-4465, 2020 | 102 | 2020 |
| Recent advances in network-based methods for disease gene prediction SK Ata, M Wu, Y Fang, L Ou-Yang, CK Kwoh, XL Li Briefings in bioinformatics 22 (4), bbaa303, 2021 | 101 | 2021 |
| Correlation-sensitive next-basket recommendation DT Le, HW Lauw, Y Fang 28th International Joint Conference on Artificial Intelligence (IJCAI 2019 …, 2019 | 99 | 2019 |
| Towards Locality-Aware Meta-Learning of Tail Node Embeddings on Networks Z Liu, W Zhang, Y Fang, X Zhang, SCH Hoi Proceedings of the 29th ACM International Conference on Information …, 2020 | 77 | 2020 |
| Adaptive Task Sampling for Meta-Learning C Liu, Z Wang, D Sahoo, Y Fang, K Zhang, SCH Hoi European Conference on Computer Vision (ECCV) 18, 752-769, 2020 | 77 | 2020 |
| Contrastive Pre-Training of GNNs on Heterogeneous Graphs X Jiang, Y Lu, Y Fang, C Shi Proceedings of the 30th ACM International Conference on Information …, 2021 | 73 | 2021 |
| Entity linking on microblogs with spatial and temporal signals Y Fang, MW Chang Transactions of ACL (TACL) 2 (Oct), 259-272, 2014 | 73 | 2014 |
| Pre-training on Large-Scale Heterogeneous Graph X Jiang, T Jia, Y Fang, C Shi, Z Lin, H Wang Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 71 | 2021 |
Chuan ShiBeijing University of Posts and TelecommunicationsVerified email at bupt.edu.cn
