| Graph neural networks: foundation, frontiers and applications L Wu, P Cui, J Pei, L Zhao, X Guo Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 304 | 2022 |
| Attentional graph convolutional networks for knowledge concept recommendation in moocs in a heterogeneous view J Gong, S Wang, J Wang, W Feng, H Peng, J Tang, PS Yu Proceedings of the 43rd international ACM SIGIR conference on research and …, 2020 | 149 | 2020 |
| Mixed-curvature multi-relational graph neural network for knowledge graph completion S Wang, X Wei, CN Nogueira dos Santos, Z Wang, R Nallapati, A Arnold, ... Proceedings of the web conference 2021, 1761-1771, 2021 | 100 | 2021 |
| Heterogeneous graph matching networks S Wang, Z Chen, X Yu, D Li, J Ni, LA Tang, J Gui, Z Li, H Chen, PS Yu arXiv preprint arXiv:1910.08074, 2019 | 83 | 2019 |
| Deep eye fixation map learning for calibration-free eye gaze tracking K Wang, S Wang, Q Ji Proceedings of the ninth biennial ACM symposium on eye tracking research …, 2016 | 76 | 2016 |
| Structural deep brain network mining S Wang, L He, B Cao, CT Lu, PS Yu, AB Ragin Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017 | 68 | 2017 |
| Kernelized support tensor machines L He, CT Lu, G Ma, S Wang, L Shen, SY Philip, AB Ragin International conference on machine learning, 1442-1451, 2017 | 62 | 2017 |
| Attentional heterogeneous graph neural network: Application to program reidentification S Wang, Z Chen, D Li, Z Li, LA Tang, J Ni, J Rhee, H Chen, PS Yu Proceedings of the 2019 SIAM International Conference on Data Mining, 693-701, 2019 | 38 | 2019 |
| Modeling sequences as distributions with uncertainty for sequential recommendation Z Fan, Z Liu, S Wang, L Zheng, PS Yu Proceedings of the 30th ACM international conference on information …, 2021 | 36 | 2021 |
| Knowledge enhanced pretrained language models: A compreshensive survey X Wei, S Wang, D Zhang, P Bhatia, A Arnold arXiv preprint arXiv:2110.08455, 2021 | 35 | 2021 |
| Entailment tree explanations via iterative retrieval-generation reasoner D Ribeiro, S Wang, X Ma, R Dong, X Wei, H Zhu, X Chen, Z Huang, P Xu, ... arXiv preprint arXiv:2205.09224, 2022 | 30 | 2022 |
| Heterogeneous graph matching networks: Application to unknown malware detection S Wang, SY Philip 2019 IEEE International Conference on Big Data (Big Data), 5401-5408, 2019 | 26 | 2019 |
| Multi-way multi-level kernel modeling for neuroimaging classification L He, CT Lu, H Ding, S Wang, L Shen, PS Yu, AB Ragin Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 25 | 2017 |
| Train your own gnn teacher: Graph-aware distillation on textual graphs C Mavromatis, VN Ioannidis, S Wang, D Zheng, S Adeshina, J Ma, H Zhao, ... Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | 19 | 2023 |
| Marginalized denoising autoencoder via graph regularization for domain adaptation Y Peng, S Wang, BL Lu Neural Information Processing: 20th International Conference, ICONIP 2013 …, 2013 | 15 | 2013 |
| STREET: A multi-task structured reasoning and explanation benchmark D Ribeiro, S Wang, X Ma, H Zhu, R Dong, D Kong, J Burger, A Ramos, ... arXiv preprint arXiv:2302.06729, 2023 | 14 | 2023 |
| H2KGAT: Hierarchical Hyperbolic Knowledge Graph Attention Network. S Wang, X Wei, CN dos Santos, Z Wang, R Nallapati, AO Arnold, B Xiang, ... EMNLP (1), 4952-4962, 2020 | 12 | 2020 |
| Deep co-investment network learning for financial assets Y Wang, C Zhang, S Wang, SY Philip, L Bai, L Cui 2018 IEEE International Conference on Big Knowledge (ICBK), 41-48, 2018 | 8 | 2018 |
| Knowledge graph representation via hierarchical hyperbolic neural graph embedding S Wang, X Wei, CN Dos Santos, Z Wang, R Nallapati, A Arnold, SY Philip 2021 IEEE International Conference on Big Data (Big Data), 540-549, 2021 | 7 | 2021 |
| Structure preserving low-rank representation for semi-supervised face recognition Y Peng, S Wang, S Wang, BL Lu Neural Information Processing: 20th International Conference, ICONIP 2013 …, 2013 | 6 | 2013 |
Philip S. YuProfessor of Computer Science, University of Illinons at Chicago在 cs.uic.edu 的电子邮件经过验证
Philip S. YuProfessor of Computer Science, University of Illinons at Chicago在 cs.uic.edu 的电子邮件经过验证