| Graph convolutional networks meet markov random fields: Semi-supervised community detection in attribute networks D Jin, Z Liu, W Li, D He, W Zhang Proceedings of the AAAI conference on artificial intelligence 33 (01), 152-159, 2019 | 145 | 2019 |
| AS-GCN: Adaptive semantic architecture of graph convolutional networks for text-rich networks Z Yu, D Jin, Z Liu, D He, X Wang, H Tong, J Han 2021 IEEE International Conference on Data Mining (ICDM), 837-846, 2021 | 60 | 2021 |
| Graph contrastive learning with generative adversarial network C Wu, C Wang, J Xu, Z Liu, K Zheng, X Wang, Y Song, K Gai Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 20 | 2023 |
| BERT2DNN: BERT distillation with massive unlabeled data for online e-commerce search Y Jiang, Y Shang, Z Liu, H Shen, Y Xiao, S Xu, W Xiong, W Yan, D Jin 2020 IEEE International Conference on Data Mining (ICDM), 212-221, 2020 | 19 | 2020 |
| Robust detection of communities with multi-semantics in large attributed networks D Jin, Z Liu, D He, B Gabrys, K Musial Knowledge Science, Engineering and Management: 11th International Conference …, 2018 | 14 | 2018 |
| Fast Unsupervised Graph Embedding via Graph Zoom Learning Z Liu, C Wang, Y Lou, H Feng 2023 IEEE 39th International Conference on Data Engineering (ICDE), 2551-2564, 2023 | 6 | 2023 |
| Knowledge Distillation based Contextual Relevance Matching for E-commerce Product Search Z Liu, C Wang, H Feng, L Wu, L Yang EMNLP 2022, 2022 | 4 | 2022 |
| Embedding text-rich graph neural networks with sequence and topical semantic structures Z Yu, D Jin, Z Liu, D He, X Wang, H Tong, J Han Knowledge and Information Systems 65 (2), 613-640, 2023 | 3 | 2023 |
| NF-VGA: Incorporating Normalizing Flows into Graph Variational Autoencoder for Embedding Attribute Networks H Shan, D Jin, P Jiao, Z Liu, B Li, Y Huang 2020 IEEE International Conference on Data Mining (ICDM), 1244-1249, 2020 | 3 | 2020 |
| 面向带属性复杂网络的鲁棒, 强解释性社团发现方法 金弟， 刘子扬， 贺瑞芳， 王啸， 何东晓 计算机学报 41 (7), 1476-1489, 2018 | 2 | 2018 |
| Incorporating dynamic temperature estimation into contrastive learning on graphs Z Liu, C Wang, L Yang, Y Lou, H Feng, C Wu, K Zheng, Y Song 2024 IEEE 40th International Conference on Data Engineering (ICDE), 2889-2903, 2024 | 1 | 2024 |
| Semi-Explicit MMoE via Heterogeneous Multi-Task Learning for Ranking Relevance Z Liu, J Chen, Y Jiang, Y Shang, W Xiong, S Xu, Z Cheng, B Long, L Wu, ... | 1 | 2021 |
| Table Embedding Models Based on Contrastive Learning for Improved Cardinality Estimation H Li, C Wang, Z Liu Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint …, 2024 | | 2024 |
| Efficient Unsupervised Graph Embedding with Attributed Graph Reduction and Dual-level Loss Z Liu, C Wang, H Feng, Z Chen IEEE Transactions on Knowledge and Data Engineering, 2024 | | 2024 |
| GraphHI: Boosting Graph Neural Networks for Large-Scale Graphs H Feng, C Wang, Z Liu, Y Lou, Z Liu, X Zhu, Y Bao, W Yan 2024 IEEE 40th International Conference on Data Engineering (ICDE), 2862-2875, 2024 | | 2024 |
| Graph Contrastive Learning with Reinforcement Augmentation Z Liu, C Wang, C Wu The 33rd International Joint Conference on Artificial Intelligence (IJCAI 2024), 2024 | | 2024 |
| TeKo: Text-Rich Graph Neural Networks With External Knowledge Z Yu, D Jin, J Wei, Y Li, Z Liu, Y Shang, J Han, L Wu IEEE Transactions on Neural Networks and Learning Systems, 2023 | | 2023 |
Di JinTianjin University, ProfessorEmail verificata su tju.edu.cn
