| Heterogeneous graph attention network X Wang, H Ji, C Shi, B Wang, Y Ye, P Cui, PS Yu The world wide web conference, 2022-2032, 2019 | 3660 | 2019 |
| A survey on network embedding P Cui, X Wang, J Pei, W Zhu IEEE transactions on knowledge and data engineering 31 (5), 833-852, 2018 | 1539 | 2018 |
| Community preserving network embedding X Wang, P Cui, J Wang, J Pei, W Zhu, S Yang Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017 | 1162 | 2017 |
| Beyond low-frequency information in graph convolutional networks D Bo, X Wang, C Shi, H Shen Proceedings of the AAAI conference on artificial intelligence 35 (5), 3950-3957, 2021 | 868 | 2021 |
| Structural deep clustering network D Bo, X Wang, C Shi, M Zhu, E Lu, P Cui Proceedings of the web conference 2020, 1400-1410, 2020 | 762 | 2020 |
| Am-gcn: Adaptive multi-channel graph convolutional networks X Wang, M Zhu, D Bo, P Cui, C Shi, J Pei Proceedings of the 26th ACM SIGKDD International conference on knowledge …, 2020 | 687 | 2020 |
| Self-supervised heterogeneous graph neural network with co-contrastive learning X Wang, N Liu, H Han, C Shi Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 568 | 2021 |
| A survey on heterogeneous graph embedding: methods, techniques, applications and sources X Wang, D Bo, C Shi, S Fan, Y Ye, PS Yu IEEE transactions on big data 9 (2), 415-436, 2022 | 559 | 2022 |
| Heterogeneous graph structure learning for graph neural networks J Zhao, X Wang, C Shi, B Hu, G Song, Y Ye Proceedings of the AAAI conference on artificial intelligence 35 (5), 4697-4705, 2021 | 365 | 2021 |
| Modularity based community detection with deep learning. L Yang, X Cao, D He, C Wang, X Wang, W Zhang IJCAI 16 (2016), 2252-2258, 2016 | 313 | 2016 |
| One2multi graph autoencoder for multi-view graph clustering S Fan, X Wang, C Shi, E Lu, K Lin, B Wang proceedings of the web conference 2020, 3070-3076, 2020 | 283 | 2020 |
| Semantic community identification in large attribute networks X Wang, D Jin, X Cao, L Yang, W Zhang Proceedings of the AAAI conference on artificial intelligence 30 (1), 2016 | 267 | 2016 |
| Structural deep embedding for hyper-networks K Tu, P Cui, X Wang, F Wang, W Zhu Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 261 | 2018 |
| Interpreting and unifying graph neural networks with an optimization framework M Zhu, X Wang, C Shi, H Ji, P Cui Proceedings of the web conference 2021, 1215-1226, 2021 | 260 | 2021 |
| Arbitrary-order proximity preserved network embedding Z Zhang, P Cui, X Wang, J Pei, X Yao, W Zhu Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018 | 247 | 2018 |
| A unified semi-supervised community detection framework using latent space graph regularization L Yang, X Cao, D Jin, X Wang, D Meng IEEE transactions on cybernetics 45 (11), 2585-2598, 2014 | 237 | 2014 |
| Deep recursive network embedding with regular equivalence K Tu, P Cui, X Wang, PS Yu, W Zhu Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018 | 230 | 2018 |
| Hyperbolic graph attention network Y Zhang, X Wang, C Shi, X Jiang, Y Ye IEEE Transactions on Big Data 8 (6), 1690-1701, 2021 | 197 | 2021 |
| Diverse non-negative matrix factorization for multiview data representation J Wang, F Tian, H Yu, CH Liu, K Zhan, X Wang IEEE transactions on cybernetics 48 (9), 2620-2632, 2017 | 191 | 2017 |
| Graph structure estimation neural networks R Wang, S Mou, X Wang, W Xiao, Q Ju, C Shi, X Xie Proceedings of the web conference 2021, 342-353, 2021 | 179 | 2021 |
