| Graph contrastive learning with adaptive augmentation Y Zhu, Y Xu, F Yu, Q Liu, S Wu, L Wang Proceedings of the web conference 2021, 2069-2080, 2021 | 1056 | 2021 |
| Deep graph contrastive representation learning Y Zhu, Y Xu, F Yu, Q Liu, S Wu, L Wang arXiv preprint arXiv:2006.04131, 2020 | 885 | 2020 |
| A dynamic recurrent model for next basket recommendation F Yu, Q Liu, S Wu, L Wang, T Tan Proceedings of the 39th International ACM SIGIR conference on Research and …, 2016 | 570 | 2016 |
| A Convolutional Approach for Misinformation Identification. F Yu, Q Liu, S Wu, L Wang, T Tan IJCAI, 3901-3907, 2017 | 460 | 2017 |
| TAGNN: Target attentive graph neural networks for session-based recommendation F Yu, Y Zhu, Q Liu, S Wu, L Wang, T Tan Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 252 | 2020 |
| A convolutional click prediction model Q Liu, F Yu, S Wu, L Wang Proceedings of the 24th ACM international on conference on information and …, 2015 | 157 | 2015 |
| Attention-based convolutional approach for misinformation identification from massive and noisy microblog posts F Yu, Q Liu, S Wu, L Wang, T Tan computers & security 83, 106-121, 2019 | 77 | 2019 |
| Mining significant microblogs for misinformation identification: an attention-based approach Q Liu, F Yu, S Wu, L Wang ACM Transactions on Intelligent Systems and Technology (TIST) 9 (5), 1-20, 2018 | 43 | 2018 |
| Deep interaction machine: A simple but effective model for high-order feature interactions F Yu, Z Liu, Q Liu, H Zhang, S Wu, L Wang Proceedings of the 29th ACM International Conference on Information …, 2020 | 32 | 2020 |
| CAGNN: Cluster-aware graph neural networks for unsupervised graph representation learning Y Zhu, Y Xu, F Yu, S Wu, L Wang arXiv preprint arXiv:2009.01674, 2020 | 31 | 2020 |
| Disentangled self-attentive neural networks for click-through rate prediction Y Xu, Y Zhu, F Yu, Q Liu, S Wu Proceedings of the 30th ACM international conference on information …, 2021 | 24 | 2021 |
| Tfnet: Multi-semantic feature interaction for ctr prediction S Wu, F Yu, X Yu, Q Liu, L Wang, T Tan, J Shao, F Huang Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 22 | 2020 |
| Disentangled item representation for recommender systems Z Cui, F Yu, S Wu, Q Liu, L Wang ACM Transactions on Intelligent Systems and Technology (TIST) 12 (2), 1-20, 2021 | 13 | 2021 |
| ICE: Information credibility evaluation on social media via representation learning Q Liu, S Wu, F Yu, L Wang, T Tan arXiv preprint arXiv:1609.09226, 2016 | 9 | 2016 |
| Global well-posedness of advective Lotka–Volterra competition systems with nonlinear diffusion Q Wang, J Yang, F Yu Proceedings of the Royal Society of Edinburgh Section A: Mathematics 150 (5 …, 2020 | 2 | 2020 |
| Boundedness in logistic Keller-Segel models with nonlinear diffusion and sensitivity functions Q Wang, J Yang, F Yu Discrete and Continuous Dynamical Systems 37 (9), 5021-5036, 2017 | 2 | 2017 |
| Robust Regularized Low-Rank Matrix Models for Regression and Classification HH Huang, F Yu, X Fan, T Zhang arXiv preprint arXiv:2205.07106, 2022 | 1 | 2022 |
| S-MolSearch: 3D Semi-supervised Contrastive Learning for Bioactive Molecule Search G Zhou, Z Wang, F Yu, G Ke, Z Wei, Z Gao arXiv preprint arXiv:2409.07462, 2024 | | 2024 |
| Multimodal Protein-Ligand Contrastive Pretraining for Effective and Efficient Drug Discovery Z Wang, Z Wang, M Yang, L Pang, F Nie, S Liu, Z Gao, G Zhao, X Ji, ... bioRxiv, 2024.08. 22.609123, 2024 | | 2024 |
| Unsupervised Graph Representation Learning with Cluster-aware Self-training and Refining Y Zhu, Y Xu, F Yu, Q Liu, S Wu ACM Transactions on Intelligent Systems and Technology 14 (5), 1-21, 2023 | | 2023 |
