| Review on knowledge graph techniques Z Xu, YP Sheng, LR He, YF Wang Journal of University of Electronic Science and Technology of China 45 (4 …, 2016 | 185 | 2016 |
| Structured Inference for Recurrent Hidden Semi-markov Model. H Liu, L He, H Bai, B Dai, K Bai, Z Xu IJCAI, 2447-2453, 2018 | 34 | 2018 |
| Neuralcp: Bayesian multiway data analysis with neural tensor decomposition B Liu, L He, Y Li, S Zhe, Z Xu Cognitive Computation 10, 1051-1061, 2018 | 31 | 2018 |
| Mutual information gradient estimation for representation learning L Wen, Y Zhou, L He, M Zhou, Z Xu arXiv preprint arXiv:2005.01123, 2020 | 27 | 2020 |
| Knowledge base completion by variational bayesian neural tensor decomposition L He, B Liu, G Li, Y Sheng, Y Wang, Z Xu Cognitive Computation 10, 1075-1084, 2018 | 27 | 2018 |
| Overview of knowledge graph technology ZL Xu, Y Sheng, L He, Y Wang Journal of University of Electronic Science and technology of China 45 (04 …, 2016 | 23 | 2016 |
| Boosting adversarial robustness via self-paced adversarial training L He, Q Ai, X Yang, Y Ren, Q Wang, Z Xu Neural Networks 167, 706-714, 2023 | 10 | 2023 |
| Generative Oversampling for Imbalanced Data via Majority-Guided VAE Q Ai, P Wang, L He, L Wen, L Pan, Z Xu International Conference on Artificial Intelligence and Statistics, 3315-3330, 2023 | 9 | 2023 |
| Edge enhancement improves adversarial robustness in image classification L He, Q Ai, Y Lei, L Pan, Y Ren, Z Xu Neurocomputing 518, 122-132, 2023 | 8 | 2023 |
| Link prediction by exploiting network formation games in exchangeable graphs L Wang, Y Wang, B Liu, L He, S Liu, G De Melo, Z Xu 2017 International Joint Conference on Neural Networks (IJCNN), 619-626, 2017 | 8 | 2017 |
| A summary of knowledge mapping technology Z Xu, YP Sheng, LR He, Y Wang Journal of Electronic Science and Technology 45 (4), 589-606, 2016 | 6 | 2016 |
| Gradient estimation of information measures in deep learning L Wen, H Bai, L He, Y Zhou, M Zhou, Z Xu Knowledge-Based Systems 224, 107046, 2021 | 5 | 2021 |
| Deep minimax probability machine L He, Z Guo, K Huang, Z Xu 2019 International Conference on Data Mining Workshops (ICDMW), 869-876, 2019 | 5 | 2019 |
| Stochastic sequential neural networks with structured inference H Liu, H Bai, L He, Z Xu arXiv preprint arXiv:1705.08695, 2017 | 5 | 2017 |
| Stein variational gradient descent with multiple kernels Q Ai, S Liu, L He, Z Xu Cognitive Computation 15 (2), 672-682, 2023 | 4 | 2023 |
| Bype-vae: Bayesian pseudocoresets exemplar vae Q Ai, L He, S Liu, Z Xu Advances in Neural Information Processing Systems 34, 5910-5920, 2021 | 3 | 2021 |
| DeepCP: Flexible nonlinear tensor decomposition B Liu, L He, S Zhe, Y Li, Z Xu NeurIPS Workshops 3, 2017 | 2 | 2017 |
| TKGR-GPRSCL: Enhance Temporal Knowledge Graph Reasoning with Graph Structure-Aware Path Representation and Supervised Contrastive Learning L Xiong, Y Sheng, L He CCF International Conference on Natural Language Processing and Chinese …, 2024 | | 2024 |
| CEGRL-TKGR: A Causal Enhanced Graph Representation Learning Framework for Improving Temporal Knowledge Graph Extrapolation Reasoning J Sun, Y Sheng, L He arXiv preprint arXiv:2408.07911, 2024 | | 2024 |
| TKGR-RHETNE: A New Temporal Knowledge Graph Reasoning Model via Jointly Modeling Relevant Historical Event and Temporal Neighborhood Event Context J Sun, Y Sheng, L Zhan, L He International Conference on Neural Information Processing, 331-343, 2023 | | 2023 |
