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 | 96 | 2020 |
Graph neural networks L Wu, P Cui, J Pei, L Zhao, L Song Graph neural networks: Foundations, frontiers, and applications, 27-37, 2022 | 78 | 2022 |
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 | 64 | 2016 |
Heterogeneous Graph Matching Networks for Unknown Malware Detection PSY Shen Wang, Zhengzhang Chen, Xiao Yu, Ding Li, Jingchao Ni, Lu-An Tang ... International Joint Conferences on Artificial Intelligence, 2019 | 62* | 2019 |
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 | 58 | 2017 |
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 | 55 | 2021 |
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 | 49 | 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 | 26 | 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 | 22 | 2021 |
Adversarial defense framework for graph neural network S Wang, Z Chen, J Ni, X Yu, Z Li, H Chen, PS Yu arXiv preprint arXiv:1905.03679, 2019 | 22 | 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 | 22 | 2017 |
Knowledge enhanced pretrained language models: A compreshensive survey X Wei, S Wang, D Zhang, P Bhatia, A Arnold arXiv preprint arXiv:2110.08455, 2021 | 17 | 2021 |
Marginalized denoising autoencoder via graph regularization for domain adaptation Y Peng, S Wang, BL Lu Neural Information Processing: 20th International Conference, ICONIP 2013 …, 2013 | 16 | 2013 |
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 | 13 | 2020 |
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 | 12 | 2022 |
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 |
Deep Co-investment Network Learning for Financial Assets Y Wang, C Zhang, S Wang, PS Yu, L Bai, L Cui 2018 IEEE International Conference on Big Knowledge (ICBK), 2018 | 5 | 2018 |
Graph neural networks in anomaly detection S Wang, PS Yu Graph Neural Networks: Foundations, Frontiers, and Applications, 557-578, 2022 | 3 | 2022 |
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 | 3 | 2021 |
Anomaly detection with graph adversarial training in computer systems Z Chen, J Gui, H Chen, J Rhee, S Wang US Patent 11,606,389, 2023 | 1 | 2023 |