Training deep neural networks on imbalanced data sets S Wang, W Liu, J Wu, L Cao, Q Meng, PJ Kennedy 2016 international joint conference on neural networks (IJCNN), 4368-4374, 2016 | 544 | 2016 |
Tri-party deep network representation S Pan, J Wu, X Zhu, C Zhang, Y Wang International Joint Conference on Artificial Intelligence 2016, 1895-1901, 2016 | 514 | 2016 |
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 | 491 | 2021 |
Stacked convolutional denoising auto-encoders for feature representation B Du, W Xiong, J Wu, L Zhang, L Zhang, D Tao IEEE transactions on cybernetics 47 (4), 1017-1027, 2016 | 435 | 2016 |
A comprehensive survey on pretrained foundation models: A history from bert to chatgpt C Zhou, Q Li, C Li, J Yu, Y Liu, G Wang, K Zhang, C Ji, Q Yan, L He, ... arXiv preprint arXiv:2302.09419, 2023 | 367 | 2023 |
Infrared and visible image fusion via detail preserving adversarial learning J Ma, P Liang, W Yu, C Chen, X Guo, J Wu, J Jiang Information Fusion 54, 85-98, 2020 | 337 | 2020 |
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 | 336 | 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 | 299 | 2021 |
Deep Learning for Community Detection: Progress, Challenges and Opportunities PSY Fanzhen Liu, Shan Xue, Jia Wu, Chuan Zhou, Wenbin Hu, Cecile Paris ... IJCAI, 4981-4987, 2020 | 261* | 2020 |
A correlation-based feature weighting filter for naive Bayes L Jiang, L Zhang, C Li, J Wu IEEE transactions on knowledge and data engineering 31 (2), 201-213, 2018 | 232 | 2018 |
Sugar: Subgraph neural network with reinforcement pooling and self-supervised mutual information mechanism Q Sun, J Li, H Peng, J Wu, Y Ning, PS Yu, L He Proceedings of the Web Conference 2021, 2081-2091, 2021 | 149 | 2021 |
Neighborhood-Aware Attentional Representation for Multilingual Knowledge Graphs. Q Zhu, X Zhou, J Wu, J Tan, L Guo ijcai, 1943-1949, 2019 | 147 | 2019 |
Nonrigid point set registration with robust transformation learning under manifold regularization J Ma, J Wu, J Zhao, J Jiang, H Zhou, QZ Sheng IEEE transactions on neural networks and learning systems 30 (12), 3584-3597, 2018 | 145 | 2018 |
A deep framework for cross-domain and cross-system recommendations F Zhu, Y Wang, C Chen, G Liu, M Orgun, J Wu arXiv preprint arXiv:2009.06215, 2020 | 136 | 2020 |
Bag constrained structure pattern mining for multi-graph classification J Wu, X Zhu, C Zhang, SY Philip Ieee transactions on knowledge and data engineering 26 (10), 2382-2396, 2014 | 131 | 2014 |
Time series feature learning with labeled and unlabeled data H Wang, Q Zhang, J Wu, S Pan, Y Chen Pattern Recognition 89, 55-66, 2019 | 125 | 2019 |
An unsupervised parameter learning model for RVFL neural network Y Zhang, J Wu, Z Cai, B Du, SY Philip Neural Networks 112, 85-97, 2019 | 122 | 2019 |
Graph structure learning with variational information bottleneck Q Sun, J Li, H Peng, J Wu, X Fu, C Ji, SY Philip Proceedings of the AAAI Conference on Artificial Intelligence 36 (4), 4165-4174, 2022 | 118 | 2022 |
Boosting for multi-graph classification J Wu, S Pan, X Zhu, Z Cai IEEE transactions on cybernetics 45 (3), 416-429, 2014 | 118 | 2014 |
Self-adaptive attribute weighting for Naive Bayes classification J Wu, S Pan, X Zhu, Z Cai, P Zhang, C Zhang Expert Systems with Applications 42 (3), 1487-1502, 2015 | 116 | 2015 |