| Textattack: A framework for adversarial attacks, data augmentation, and adversarial training in nlp JX Morris, E Lifland, JY Yoo, J Grigsby, D Jin, Y Qi arXiv preprint arXiv:2005.05909, 2020 | 742 | 2020 |
| A comprehensive survey on graph anomaly detection with deep learning X Ma, J Wu, S Xue, J Yang, C Zhou, QZ Sheng, H Xiong, L Akoglu IEEE Transactions on Knowledge and Data Engineering 35 (12), 12012-12038, 2021 | 641 | 2021 |
| What disease does this patient have? a large-scale open domain question answering dataset from medical exams D Jin, E Pan, N Oufattole, WH Weng, H Fang, P Szolovits Applied Sciences 11 (14), 6421, 2021 | 489 | 2021 |
| A comprehensive survey on community detection with deep learning X Su, S Xue, F Liu, J Wu, J Yang, C Zhou, W Hu, C Paris, S Nepal, D Jin, ... IEEE Transactions on Neural Networks and Learning Systems, 2022 | 401 | 2022 |
| A survey of community detection approaches: From statistical modeling to deep learning D Jin, Z Yu, P Jiao, S Pan, D He, J Wu, SY Philip, W Zhang IEEE Transactions on Knowledge and Data Engineering 35 (2), 1149-1170, 2021 | 357 | 2021 |
| 复杂网络聚类方法 杨博 [1， 刘大有 [1， 金弟 [1， 马海宾 [1 软件学报 20 (1), 54-66, 2009 | 268* | 2009 |
| Graph neural networks for graphs with heterophily: A survey X Zheng, Y Wang, Y Liu, M Li, M Zhang, D Jin, PS Yu, S Pan arXiv preprint arXiv:2202.07082, 2022 | 248 | 2022 |
| 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 | 236 | 2016 |
| 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 | 228 | 2014 |
| Heterogeneous graph neural network via attribute completion D Jin, C Huo, C Liang, L Yang Proceedings of the web conference 2021, 391-400, 2021 | 179 | 2021 |
| Graph convolutional networks meet markov random fields: Semi-supervised community detection in attribute networks D Jin, Z Liu, W Li, D He, W Zhang Proceedings of the AAAI conference on artificial intelligence 33 (01), 152-159, 2019 | 147 | 2019 |
| Powerful graph convolutional networks with adaptive propagation mechanism for homophily and heterophily T Wang, D Jin, R Wang, D He, Y Huang Proceedings of the AAAI conference on artificial intelligence 36 (4), 4210-4218, 2022 | 116 | 2022 |
| Adaptive community detection incorporating topology and content in social networks M Qin, D Jin, D He, B Gabrys, K Musial Proceedings of the 2017 IEEE/ACM International Conference on Advances in …, 2017 | 113 | 2017 |
| Joint identification of network communities and semantics via integrative modeling of network topologies and node contents D He, Z Feng, D Jin, X Wang, W Zhang Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 111 | 2017 |
| Universal graph convolutional networks D Jin, Z Yu, C Huo, R Wang, X Wang, D He, J Han Advances in Neural Information Processing Systems 34, 10654-10664, 2021 | 104 | 2021 |
| Community-centric graph convolutional network for unsupervised community detection D He, Y Song, D Jin, Z Feng, B Zhang, Z Yu, W Zhang Proceedings of the twenty-ninth international conference on international …, 2021 | 103 | 2021 |
| A Markov random walk under constraint for discovering overlapping communities in complex networks D Jin, B Yang, C Baquero, D Liu, D He, J Liu Journal of Statistical Mechanics: Theory and Experiment 2011 (05), P05031, 2011 | 103 | 2011 |
| Identifying overlapping communities as well as hubs and outliers via nonnegative matrix factorization X Cao, X Wang, D Jin, Y Cao, D He Scientific reports 3 (1), 2993, 2013 | 102 | 2013 |
| Topology Optimization based Graph Convolutional Network. L Yang, Z Kang, X Cao, Di Jin 0001, B Yang, Y Guo IJCAI, 4054-4061, 2019 | 101 | 2019 |
| Semi-supervised community detection based on non-negative matrix factorization with node popularity X Liu, W Wang, D He, P Jiao, D Jin, CV Cannistraci Information Sciences 381, 304-321, 2017 | 84 | 2017 |
Dongxiao HeTianjin University, Professor of Computer ScienceEmail verificata su tju.edu.cn
