| Activity recognition and abnormality detection with the switching hidden semi-markov model TV Duong, HH Bui, DQ Phung, S Venkatesh 2005 IEEE Computer Society Conference on Computer Vision and Pattern …, 2005 | 701 | 2005 |
| Labeled random finite sets and the Bayes multi-target tracking filter BN Vo, BT Vo, D Phung IEEE Transaction on Signal Processing, 2014 | 522 | 2014 |
| Learning and detecting activities from movement trajectories using the hierarchical hidden Markov model N Nguyen, DQ Phung, S Venkatesh, H Bui Computer Vision and Pattern Recognition, 2005. CVPR 2005. IEEE Computer …, 2005 | 450 | 2005 |
| Guidelines for developing and reporting machine learning predictive models in biomedical research: a multidisciplinary view W Luo, D Phung, T Tran, S Gupta, S Rana, C Karmakar, A Shilton, ... Journal of medical Internet research 18 (12), e323, 2016 | 228 | 2016 |
| A novel embedding model for knowledge base completion based on convolutional neural network DQ Nguyen, TD Nguyen, DQ Nguyen, D Phung arXiv preprint arXiv:1712.02121, 2017 | 216 | 2017 |
| Deepcare: A deep dynamic memory model for predictive medicine T Pham, T Tran, D Phung, S Venkatesh Pacific-Asia conference on knowledge discovery and data mining, 30-41, 2016 | 214 | 2016 |
| Predicting healthcare trajectories from medical records: A deep learning approach T Pham, T Tran, D Phung, S Venkatesh Journal of biomedical informatics 69, 218-229, 2017 | 212 | 2017 |
| Dual discriminator generative adversarial nets TD Nguyen, T Le, H Vu, D Phung arXiv preprint arXiv:1709.03831, 2017 | 177 | 2017 |
| MGAN: Training generative adversarial nets with multiple generators Q Hoang, TD Nguyen, T Le, D Phung International Conference on Learning Representation (ICLR), 2018 | 164* | 2018 |
| Affective and Content Analysis of Online Depression Communities T Nguyen, D Phung, B Dao, S Venkatesh, M Berk IEEE Transaction on Affective Computing, 1-1, 2014 | 150 | 2014 |
| Efficient duration and hierarchical modeling for human activity recognition T Duong, D Phung, H Bui, S Venkatesh Artificial Intelligence 173 (7-8), 830-856, 2009 | 134 | 2009 |
| Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM) T Tran, TD Nguyen, D Phung, S Venkatesh Journal of biomedical informatics 54, 96-105, 2015 | 123 | 2015 |
| Hierarchical hidden Markov models with general state hierarchy HH Bui, DQ Phung, S Venkatesh Proceedings of the national conference on artificial intelligence, 324-329, 2004 | 119 | 2004 |
| Column networks for collective classification T Pham, T Tran, D Phung, S Venkatesh Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 115 | 2017 |
| Risk stratification using data from electronic medical records better predicts suicide risks than clinician assessments T Tran, W Luo, D Phung, R Harvey, M Berk, RL Kennedy, S Venkatesh BMC psychiatry 14 (1), 1-9, 2014 | 103 | 2014 |
| Nonnegative shared subspace learning and its application to social media retrieval SK Gupta, D Phung, B Adams, T Tran, S Venkatesh Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010 | 85 | 2010 |
| A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization DQ Nguyen, T Vu, TD Nguyen, DQ Nguyen, D Phung Annual Conference of the North American Chapter of the Association for …, 2019 | 77* | 2019 |
| Multilevel clustering via Wasserstein means N Ho, XL Nguyen, M Yurochkin, HH Bui, V Huynh, D Phung International Conference on Machine Learning, 1501-1509, 2017 | 71 | 2017 |
| Sensing and using social context B Adams, D Phung, S Venkatesh ACM Transactions on Multimedia Computing, Communications, and Applications …, 2008 | 68 | 2008 |
| Ordinal Boltzmann machines for collaborative filtering T Tran, DQ Phung, S Venkatesh Arxiv preprint arXiv:1205.2611, 2009 | 67* | 2009 |
