Hierarchical adaptive deep convolution neural network and its application to bearing fault diagnosis X Guo, L Chen, C Shen Measurement 93, 490-502, 2016 | 681 | 2016 |
Graph neural networks for natural language processing: A survey L Wu, Y Chen, K Shen, X Guo, H Gao, S Li, J Pei, B Long Foundations and Trends® in Machine Learning 16 (2), 119-328, 2023 | 97 | 2023 |
A systematic survey on deep generative models for graph generation X Guo, L Zhao IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 | 73 | 2022 |
Deep fault recognizer: An integrated model to denoise and extract features for fault diagnosis in rotating machinery X Guo, C Shen, L Chen Applied Sciences 7 (1), 41, 2016 | 71 | 2016 |
Deep graph translation X Guo, L Wu, L Zhao IEEE Transactions on Neural Networks and Learning Systems, 2022 | 50 | 2022 |
A hybrid technique based on convolutional neural network and support vector regression for intelligent diagnosis of rotating machinery W You, C Shen, X Guo, X Jiang, J Shi, Z Zhu Advances in Mechanical Engineering 9 (6), 1687814017704146, 2017 | 40 | 2017 |
Interpretable deep graph generation with node-edge co-disentanglement X Guo, L Zhao, Z Qin, L Wu, A Shehu, Y Ye Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 32 | 2020 |
Graphgt: Machine learning datasets for graph generation and transformation Y Du, S Wang, X Guo, H Cao, S Hu, J Jiang, A Varala, A Angirekula, ... Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021 | 31 | 2021 |
Distant-supervision of heterogeneous multitask learning for social event forecasting with multilingual indicators L Zhao, J Wang, X Guo Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 28 | 2018 |
Generating tertiary protein structures via an interpretative variational autoencoder X Guo, Y Du, S Tadepalli, L Zhao, A Shehu arXiv preprint arXiv:2004.07119, 2020 | 24 | 2020 |
Deep multi-attributed graph translation with node-edge co-evolution X Guo, L Zhao, C Nowzari, S Rafatirad, H Homayoun, SMP Dinakarrao 2019 IEEE International Conference on Data Mining (ICDM), 250-259, 2019 | 24 | 2019 |
Property controllable variational autoencoder via invertible mutual dependence X Guo, Y Du, L Zhao International Conference on Learning Representations, 2021 | 20 | 2021 |
Deep generative models for spatial networks X Guo, Y Du, L Zhao Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 19 | 2021 |
Cognitive and scalable technique for securing IoT networks against malware epidemics SMP Dinakarrao, X Guo, H Sayadi, C Nowzari, A Sasan, S Rafatirad, ... IEEE Access 8, 138508-138528, 2020 | 19 | 2020 |
Disentangled spatiotemporal graph generative models Y Du, X Guo, H Cao, Y Ye, L Zhao Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6541-6549, 2022 | 14 | 2022 |
Interpretable molecular graph generation via monotonic constraints Y Du, X Guo, A Shehu, L Zhao Proceedings of the 2022 SIAM International Conference on Data Mining (SDM …, 2022 | 14 | 2022 |
Deep generative model for periodic graphs S Wang, X Guo, L Zhao arXiv preprint arXiv:2201.11932, 2022 | 13 | 2022 |
Multi-stage deep classifier cascades for open world recognition X Guo, A Alipour-Fanid, L Wu, H Purohit, X Chen, K Zeng, L Zhao Proceedings of the 28th ACM International Conference on Information and …, 2019 | 13 | 2019 |
Human face recognition based on adaptive deep Convolution Neural Network L Chen, X Guo, C Geng 2016 35th Chinese Control Conference (CCC), 6967-6970, 2016 | 12 | 2016 |
Deep latent-variable models for controllable molecule generation Y Du, Y Wang, F Alam, Y Lu, X Guo, L Zhao, A Shehu 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2021 | 10 | 2021 |