| Risk prediction on electronic health records with prior medical knowledge F Ma, J Gao, Q Suo, Q You, J Zhou, A Zhang Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 145 | 2018 |
| Deep patient similarity learning for personalized healthcare Q Suo, F Ma, Y Yuan, M Huai, W Zhong, J Gao, A Zhang IEEE transactions on nanobioscience 17 (3), 219-227, 2018 | 141 | 2018 |
| Personalized disease prediction using a CNN-based similarity learning method Q Suo, F Ma, Y Yuan, M Huai, W Zhong, A Zhang, J Gao 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2017 | 105 | 2017 |
| A novel channel-aware attention framework for multi-channel eeg seizure detection via multi-view deep learning Y Yuan, G Xun, F Ma, Q Suo, H Xue, K Jia, A Zhang 2018 IEEE EMBS international conference on biomedical & health informatics …, 2018 | 92 | 2018 |
| A multi-task framework for monitoring health conditions via attention-based recurrent neural networks Q Suo, F Ma, G Canino, J Gao, A Zhang, P Veltri, G Agostino AMIA annual symposium proceedings 2017, 1665, 2017 | 76 | 2017 |
| Wave2vec: Deep representation learning for clinical temporal data Y Yuan, G Xun, Q Suo, K Jia, A Zhang Neurocomputing 324, 31-42, 2019 | 67 | 2019 |
| Tadanet: Task-adaptive network for graph-enriched meta-learning Q Suo, J Chou, W Zhong, A Zhang Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 55 | 2020 |
| Metric learning on healthcare data with incomplete modalities. Q Suo, W Zhong, F Ma, Y Yuan, J Gao, A Zhang IJCAI 3534, 3540, 2019 | 46 | 2019 |
| Recurrent imputation for multivariate time series with missing values Q Suo, L Yao, G Xun, J Sun, A Zhang 2019 IEEE international conference on healthcare informatics (ICHI), 1-3, 2019 | 43 | 2019 |
| Wave2vec: Learning deep representations for biosignals Y Yuan, G Xun, Q Suo, K Jia, A Zhang 2017 IEEE International Conference on Data Mining (ICDM), 1159-1164, 2017 | 40 | 2017 |
| Improving task-free continual learning by distributionally robust memory evolution Z Wang, L Shen, L Fang, Q Suo, T Duan, M Gao International conference on machine learning, 22985-22998, 2022 | 38 | 2022 |
| Multi-task sparse metric learning for monitoring patient similarity progression Q Suo, W Zhong, F Ma, Y Ye, M Huai, A Zhang 2018 IEEE International Conference on Data Mining (ICDM), 477-486, 2018 | 30 | 2018 |
| Heterogeneous spatio-temporal graph convolution network for traffic forecasting with missing values W Zhong, Q Suo, X Jia, A Zhang, L Su 2021 IEEE 41st International Conference on Distributed Computing Systems …, 2021 | 28 | 2021 |
| Uncorrelated patient similarity learning M Huai, C Miao, Q Suo, Y Li, J Gao, A Zhang Proceedings of the 2018 SIAM International Conference on Data Mining, 270-278, 2018 | 28 | 2018 |
| GLIMA: Global and local time series imputation with multi-directional attention learning Q Suo, W Zhong, G Xun, J Sun, C Chen, A Zhang 2020 IEEE International Conference on Big Data (Big Data), 798-807, 2020 | 26 | 2020 |
| Risk factor analysis based on deep learning models Q Suo, H Xue, J Gao, A Zhang Proceedings of the 7th ACM International Conference on Bioinformatics …, 2016 | 25 | 2016 |
| Meta-learning without data via wasserstein distributionally-robust model fusion Z Wang, X Wang, L Shen, Q Suo, K Song, D Yu, Y Shen, M Gao Uncertainty in Artificial Intelligence, 2045-2055, 2022 | 22 | 2022 |
| Meta learning on a sequence of imbalanced domains with difficulty awareness Z Wang, T Duan, L Fang, Q Suo, M Gao Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 21 | 2021 |
| Metric learning from probabilistic labels M Huai, C Miao, Y Li, Q Suo, L Su, A Zhang Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018 | 20 | 2018 |
| A reliability-aware vehicular crowdsensing system for pothole profiling W Zhong, Q Suo, F Ma, Y Hou, A Gupta, C Qiao, L Su Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2019 | 17 | 2019 |
Aidong Zhang, Fellow of ACM, IEEE, a...Thomas M. Linville Professor of Computer Science, University of Virginia在 virginia.edu 的电子邮件经过验证
