| Video abstraction: A systematic review and classification BT Truong, S Venkatesh ACM transactions on multimedia computing, communications, and applications …, 2007 | 1110 | 2007 |
| 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 | 829 | 2016 |
| 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 | 782 | 2005 |
| GraphDTA: predicting drug–target binding affinity with graph neural networks T Nguyen, H Le, TP Quinn, T Nguyen, TD Le, S Venkatesh Bioinformatics 37 (8), 1140-1147, 2021 | 743 | 2021 |
| 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 | 542 | 2017 |
| Learning and detecting activities from movement trajectories using the hierarchical hidden Markov model NT Nguyen, DQ Phung, S Venkatesh, H Bui 2005 IEEE Computer Society Conference on Computer Vision and Pattern …, 2005 | 503 | 2005 |
| : A Convolutional Net for Medical Records P Nguyen, T Tran, N Wickramasinghe, S Venkatesh IEEE journal of biomedical and health informatics 21 (1), 22-30, 2016 | 454 | 2016 |
| Policy recognition in the abstract hidden markov model HH Bui, S Venkatesh, G West Journal of Artificial Intelligence Research 17, 451-499, 2002 | 403 | 2002 |
| Deepcare: A deep dynamic memory model for predictive medicine T Pham, T Tran, D Phung, S Venkatesh Advances in Knowledge Discovery and Data Mining: 20th Pacific-Asia …, 2016 | 401 | 2016 |
| Bayesian optimization for adaptive experimental design: A review S Greenhill, S Rana, S Gupta, P Vellanki, S Venkatesh IEEE access 8, 13937-13948, 2020 | 386 | 2020 |
| Fast cross-validation algorithms for least squares support vector machine and kernel ridge regression S An, W Liu, S Venkatesh Pattern Recognition 40 (8), 2154-2162, 2007 | 370 | 2007 |
| Learning regularity in skeleton trajectories for anomaly detection in videos R Morais, V Le, T Tran, B Saha, M Mansour, S Venkatesh Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 341 | 2019 |
| Hierarchical conditional relation networks for video question answering TM Le, V Le, S Venkatesh, T Tran Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 307 | 2020 |
| Joint learning and dictionary construction for pattern recognition DS Pham, S Venkatesh 2008 IEEE conference on computer vision and pattern recognition, 1-8, 2008 | 301 | 2008 |
| Outbreak investigation of Nipah virus disease in Kerala, India, 2018 G Arunkumar, R Chandni, DT Mourya, SK Singh, R Sadanandan, ... The Journal of infectious diseases 219 (12), 1867-1878, 2019 | 300 | 2019 |
| How honeybees make grazing landings on flat surfaces MV Srinivasan, SW Zhang, JS Chahl, E Barth, S Venkatesh Biological cybernetics 83, 171-183, 2000 | 300 | 2000 |
| Face recognition using kernel ridge regression S An, W Liu, S Venkatesh 2007 IEEE conference on computer vision and pattern recognition, 1-7, 2007 | 285 | 2007 |
| Affective and content analysis of online depression communities T Nguyen, D Phung, B Dao, S Venkatesh, M Berk IEEE transactions on affective computing 5 (3), 217-226, 2014 | 284 | 2014 |
| Robot navigation inspired by principles of insect vision MV Srinivasan, JS Chahl, K Weber, S Venkatesh, MG Nagle, SW Zhang Robotics and Autonomous Systems 26 (2-3), 203-216, 1999 | 267 | 1999 |
| Toward clinical digital phenotyping: a timely opportunity to consider purpose, quality, and safety K Huckvale, S Venkatesh, H Christensen NPJ digital medicine 2 (1), 1-11, 2019 | 264 | 2019 |
