| Representation Learning for Attributed Multiplex Heterogeneous Network Y Cen, X Zou, J Zhang, H Yang, J Zhou, J Tang Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019 | 369 | 2019 |
| Towards Knowledge-Based Recommender Dialog System Q Chen, J Lin, Y Zhang, M Ding, Y Cen, H Yang, J Tang Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 170 | 2019 |
| Controllable Multi-Interest Framework for Recommendation Y Cen, J Zhang, X Zou, C Zhou, H Yang, J Tang Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 163 | 2020 |
| GraphMAE: Self-Supervised Masked Graph Autoencoders Z Hou, X Liu, Y Cen, Y Dong, H Yang, C Wang, J Tang Proceedings of the 28th ACM SIGKDD international conference on knowledge …, 2022 | 111 | 2022 |
| Wudaocorpora: A super large-scale chinese corpora for pre-training language models S Yuan, H Zhao, Z Du, M Ding, X Liu, Y Cen, X Zou, Z Yang, J Tang AI Open 2, 65-68, 2021 | 41* | 2021 |
| Cogdl: A comprehensive library for graph deep learning Y Cen, Z Hou, Y Wang, Q Chen, Y Luo, Z Yu, H Zhang, X Yao, A Zeng, ... Proceedings of the ACM Web Conference 2023, 747-758, 2023 | 38* | 2023 |
| Trust relationship prediction in alibaba E-commerce platform Y Cen, J Zhang, G Wang, Y Qian, C Meng, Z Dai, H Yang, J Tang IEEE Transactions on Knowledge and Data Engineering 32 (5), 1024-1035, 2019 | 32 | 2019 |
| Graph robustness benchmark: Benchmarking the adversarial robustness of graph machine learning Q Zheng, X Zou, Y Dong, Y Cen, D Yin, J Xu, Y Yang, J Tang arXiv preprint arXiv:2111.04314, 2021 | 23 | 2021 |
| Mask and reason: Pre-training knowledge graph transformers for complex logical queries X Liu, S Zhao, K Su, Y Cen, J Qiu, M Zhang, W Wu, Y Dong, J Tang Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 18 | 2022 |
| GACT: Activation compressed training for generic network architectures X Liu, L Zheng, D Wang, Y Cen, W Chen, X Han, J Chen, Z Liu, J Tang, ... International Conference on Machine Learning, 14139-14152, 2022 | 12* | 2022 |
| SCR: Training Graph Neural Networks with Consistency Regularization C Zhang, Y He, Y Cen, Z Hou, W Feng, Y Dong, X Cheng, H Cai, F He, ... arXiv preprint arXiv:2112.04319, 2021 | 9 | 2021 |
| Automated unsupervised graph representation learning Z Hou, Y Cen, Y Dong, J Zhang, J Tang IEEE Transactions on Knowledge and Data Engineering, 2021 | 9 | 2021 |
| Graph representation learning: foundations, methods, applications and systems W Jin, Y Ma, Y Wang, X Liu, J Tang, Y Cen, J Qiu, J Tang, C Shi, Y Ye, ... Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 3 | 2021 |
| BatchSampler: Sampling Mini-Batches for Contrastive Learning in Vision, Language, and Graphs Z Yang, T Huang, M Ding, Y Dong, R Ying, Y Cen, Y Geng, J Tang arXiv preprint arXiv:2306.03355, 2023 | 2 | 2023 |
| GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner Z Hou, Y He, Y Cen, X Liu, Y Dong, E Kharlamov, J Tang Proceedings of the ACM Web Conference 2023, 737-746, 2023 | 2 | 2023 |
| Local Clustering Graph Neural Networks J Qiu, Y Cen, Q Chen, C Zhou, J Zhou, H Yang, J Tang | 1 | 2020 |
| MTDiag: an effective multi-task framework for automatic diagnosis Z Hou, Y Cen, Z Liu, D Wu, B Wang, X Li, L Hong, J Tang Proceedings of the AAAI Conference on Artificial Intelligence 37 (12), 14241 …, 2023 | | 2023 |
| Rethinking the setting of semi-supervised learning on graphs Z Li, M Ding, W Li, Z Wang, Z Zeng, Y Cen, J Tang arXiv preprint arXiv:2205.14403, 2022 | | 2022 |
| MDGNN: METAPATH-BASED DECOUPLED GRAPH NEURAL NETWORK FOR MAG240M-LSC H Zhao, Y Cen, Y He, Z Hou, X Liu, X Cheng | | |
Tang JieProfessor, Tsinghua UniversityZweryfikowany adres z tsinghua.edu.cn
