| Relation structure-aware heterogeneous graph neural network S Zhu, C Zhou, S Pan, X Zhu, B Wang 2019 IEEE international conference on data mining (ICDM), 1534-1539, 2019 | 128 | 2019 |
| Graph Geometry Interaction Learning S Zhu, S Pan, C Zhou, J Wu, Y Cao, B Wang arXiv preprint arXiv:2010.12135, 2020 | 96 | 2020 |
| DSN-DDI: an accurate and generalized framework for drug–drug interaction prediction by dual-view representation learning Z Li, S Zhu, B Shao, X Zeng, T Wang, TY Liu Briefings in Bioinformatics 24 (1), bbac597, 2023 | 59 | 2023 |
| Multi-graph fusion networks for urban region embedding S Wu, X Yan, X Fan, S Pan, S Zhu, C Zheng, M Cheng, C Wang arXiv preprint arXiv:2201.09760, 2022 | 43 | 2022 |
| Ultrahyperbolic Knowledge Graph Embeddings B Xiong, S Zhu, M Nayyeri, C Xu, S Pan, C Zhou, S Staab arXiv preprint arXiv:2206.00449, 2022 | 38 | 2022 |
| Pseudo-riemannian graph convolutional networks B Xiong, S Zhu, N Potyka, S Pan, C Zhou, S Staab Advances in Neural Information Processing Systems 35, 3488-3501, 2022 | 34* | 2022 |
| GSSNN: Graph smoothing splines neural networks S Zhu, L Zhou, S Pan, C Zhou, G Yan, B Wang Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 7007-7014, 2020 | 19 | 2020 |
| Multi-view substructure learning for drug-drug interaction prediction Z Li, S Zhu, B Shao, TY Liu, X Zeng, T Wang arXiv preprint arXiv:2203.14513, 2022 | 2 | 2022 |
| RHGNN: imposing relational inductive bias for heterogeneous graph neural network S Zhu, S Zhang, Y Liu, C Zhou, S Pan, Z Li, H Chen International Journal of Machine Learning and Cybernetics, 1-17, 2024 | 1 | 2024 |
| Geometry contrastive learning on heterogeneous graphs S Zhu, C Zhou, A Cheng, S Pan, S Wang, D Yin, B Wang arXiv preprint arXiv:2206.12547, 2022 | 1 | 2022 |
