| Parameterized explainer for graph neural network D Luo, W Cheng, D Xu, W Yu, B Zong, H Chen, X Zhang Advances in neural information processing systems 33, 19620-19631, 2020 | 1004 | 2020 |
| Learning to Drop: Robust Graph Neural Network via Topological Denoising D Luo, W Cheng, W Yu, B Zong, J Ni, H Chen, X Zhang Proceedings of the 14th ACM international conference on web search and data …, 2021 | 361 | 2021 |
| Infogcl: Information-aware graph contrastive learning D Xu, W Cheng, D Luo, H Chen, X Zhang Advances in Neural Information Processing Systems 34, 30414-30425, 2021 | 293 | 2021 |
| Spatio-temporal attentive RNN for node classification in temporal attributed graphs. D Xu, W Cheng, D Luo, X Liu, X Zhang IJCAI, 3947-3953, 2019 | 122 | 2019 |
| Time series contrastive learning with information-aware augmentations D Luo, W Cheng, Y Wang, D Xu, J Ni, W Yu, X Zhang, Y Liu, Y Chen, ... Proceedings of the AAAI Conference on Artificial Intelligence 37 (4), 4534-4542, 2023 | 121 | 2023 |
| Local community detection in multiple networks D Luo, Y Bian, Y Yan, X Liu, J Huan, X Zhang Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 70 | 2020 |
| Mogat: a multi-omics integration framework using graph attention networks for cancer subtype prediction RB Tanvir, MM Islam, M Sobhan, D Luo, AM Mondal International Journal of Molecular Sciences 25 (5), 2788, 2024 | 53 | 2024 |
| Adaptive neural network for node classification in dynamic networks D Xu, W Cheng, D Luo, Y Gu, X Liu, J Ni, B Zong, H Chen, X Zhang 2019 IEEE International Conference on Data Mining (ICDM), 1402-1407, 2019 | 49 | 2019 |
| Mixupexplainer: Generalizing explanations for graph neural networks with data augmentation J Zhang, D Luo, H Wei Proceedings of the 29th ACM SIGKDD conference on knowledge discovery and …, 2023 | 47 | 2023 |
| Deep Multi-Graph Clustering via Attentive Cross-Graph Association D Luo, J Ni, S Wang, Y Bian, X Yu, X Zhang Proceedings of the 13th International Conference on Web Search and Data …, 2020 | 41 | 2020 |
| Constrained local graph clustering by colored random walk Y Yan, Y Bian, D Luo, D Lee, X Zhang The world wide web conference, 2137-2146, 2019 | 38 | 2019 |
| On multi-query local community detection Y Bian, Y Yan, W Cheng, W Wang, D Luo, X Zhang 2018 IEEE international conference on data mining (ICDM), 9-18, 2018 | 37 | 2018 |
| Parametric Augmentation for Time Series Contrastive Learning X Zheng, T Wang, W Cheng, A Ma, H Chen, M Sha, D Luo International Conference on Learning Representations (ICLR), 2024 | 35* | 2024 |
| TimeX++: Learning Time-Series Explanations with Information Bottleneck Z Liu, T Wang, J Shi, X Zheng, Z Chen, L Song, W Dong, J Obeysekera, ... Forty-first International Conference on Machine Learning, 2024 | 33 | 2024 |
| Towards robust fidelity for evaluating explainability of graph neural networks X Zheng, F Shirani, T Wang, W Cheng, Z Chen, H Chen, H Wei, D Luo The Twelfth International Conference on Learning Representations, 2024 | 33 | 2024 |
| Towards Faithful and Consistent Explanations for Graph Neural Networks T Zhao, D Luo, X Zhang, S Wang Proceedings of the Sixteenth ACM International Conference on Web Search and …, 2023 | 33* | 2023 |
| Personalized federated learning via heterogeneous modular networks T Wang, W Cheng, D Luo, W Yu, J Ni, L Tong, H Chen, X Zhang 2022 IEEE International Conference on Data Mining (ICDM), 1197-1202, 2022 | 30 | 2022 |
| MEDPLAN: A Two-Stage RAG-Based System for Personalized Medical Plan Generation HL Hsu, CT Dao, L Wang, Z Shuai, TNM Phan, JE Ding, CC Liao, P Hu, ... ACL Industry Track, 2025 | 27 | 2025 |
| Large language multimodal models for new-onset type 2 diabetes prediction using five-year cohort electronic health records JE Ding, PNM Thao, WC Peng, JZ Wang, CC Chug, MC Hsieh, YC Tseng, ... Scientific reports 14 (1), 20774, 2024 | 26 | 2024 |
| Harnessing Vision Models for Time Series Analysis: A Survey J Ni, Z Zhao, CA Shen, H Tong, D Song, W Cheng, D Luo, H Chen IJCAI Survey Track, 2025 | 25 | 2025 |
Wei ChengSenior Research Staff Member, NEC Laboratories America (Ph.D, UNC-Chapel Hill)Verified email at nec-labs.com
