| Link prediction based on graph neural networks M Zhang, Y Chen Advances in Neural Information Processing Systems 31, 5165-5175, 2018 | 1269 | 2018 |
| An End-to-End Deep Learning Architecture for Graph Classification M Zhang, Z Cui, M Neumann, Y Chen AAAI, 4438-4445, 2018 | 1188 | 2018 |
| Weisfeiler-Lehman Neural Machine for Link Prediction M Zhang, Y Chen Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 190 | 2017 |
| Inductive matrix completion based on graph neural networks M Zhang, Y Chen International Conference on Learning Representations (ICLR 2020), 2020 | 183 | 2020 |
| Braingnn: Interpretable brain graph neural network for fmri analysis X Li, Y Zhou, N Dvornek, M Zhang, S Gao, J Zhuang, D Scheinost, ... Medical Image Analysis 74, 102233, 2021 | 159 | 2021 |
| D-vae: A variational autoencoder for directed acyclic graphs M Zhang, S Jiang, Z Cui, R Garnett, Y Chen Advances in Neural Information Processing Systems, 1588-1600, 2019 | 115 | 2019 |
| Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning M Zhang, P Li, Y Xia, K Wang, L Jin Advances in Neural Information Processing Systems 34, 2021 | 105* | 2021 |
| Beyond Link Prediction: Predicting Hyperlinks in Adjacency Space M Zhang, Z Cui, S Jiang, Y Chen AAAI, 4430-4437, 2018 | 94* | 2018 |
| Decoupling the Depth and Scope of Graph Neural Networks H Zeng, M Zhang, Y Xia, A Srivastava, A Malevich, R Kannan, V Prasanna, ... Advances in Neural Information Processing Systems 34, 2021 | 76* | 2021 |
| Batch mode active learning for regression with expected model change W Cai, M Zhang, Y Zhang IEEE transactions on neural networks and learning systems 28 (7), 1668-1681, 2017 | 69 | 2017 |
| Deep-learning model for predicting 30-day postoperative mortality BA Fritz, Z Cui, M Zhang, Y He, Y Chen, A Kronzer, AB Abdallah, CR King, ... British Journal of Anaesthesia 123 (5), 688-695, 2019 | 67 | 2019 |
| Nested Graph Neural Networks M Zhang, P Li Advances in Neural Information Processing Systems 34, 2021 | 55 | 2021 |
| Boostgapfill: Improving the fidelity of metabolic network reconstructions through integrated constraint and pattern-based methods T Oyetunde, M Zhang, Y Chen, Y Tang, C Lo Bioinformatics 33 (4), 608-611, 2017 | 41 | 2017 |
| Pooling regularized graph neural network for fmri biomarker analysis X Li, Y Zhou, NC Dvornek, M Zhang, J Zhuang, P Ventola, JS Duncan Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 35 | 2020 |
| WUFlux: an open-source platform for 13 C metabolic flux analysis of bacterial metabolism L He, SG Wu, M Zhang, Y Chen, YJ Tang BMC bioinformatics 17 (1), 1-7, 2016 | 34 | 2016 |
| Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks H Wang, H Yin, M Zhang, P Li International Conference on Learning Representations, 2021 | 24 | 2021 |
| How powerful are spectral graph neural networks X Wang, M Zhang International Conference on Machine Learning, 23341-23362, 2022 | 20 | 2022 |
| Hierarchical Attention Propagation for Healthcare Representation Learning M Zhang, CR King, M Avidan, Y Chen Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 19 | 2020 |
| Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning H Yin, M Zhang, Y Wang, J Wang, P Li arXiv preprint arXiv:2202.13538, 2022 | 12 | 2022 |
| Active learning for ranking with sample density W Cai, M Zhang, Y Zhang Information Retrieval Journal 18 (2), 123-144, 2015 | 11 | 2015 |
Yixin ChenProfessor of Computer Science, Washington University | IEEE FellowVerified email at cse.wustl.edu
