Dinh Phung
Dinh Phung
Professor, Monash University and Chief AI Scientist, Trusting Social
Verified email at monash.edu - Homepage
TitleCited byYear
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
6032005
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
4072005
Labeled random finite sets and the Bayes multi-target tracking filter
BN Vo, BT Vo, D Phung
IEEE Transaction on Signal Processing, 2014
3392014
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
1122009
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
1082004
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
982016
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
832014
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
702010
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
642016
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), 76, 2014
632014
Sensing and using social context
B Adams, D Phung, S Venkatesh
ACM Transactions on Multimedia Computing, Communications, and Applications …, 2008
622008
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
572017
Extraction of social context and application to personal multimedia exploration
B Adams, D Phung, S Venkatesh
Proceedings of the 14th ACM international conference on Multimedia, 987-996, 2006
572006
Dual discriminator generative adversarial nets
T Nguyen, T Le, H Vu, D Phung
Advances in Neural Information Processing Systems, 2670-2680, 2017
562017
Flickr hypergroups
RA Negoescu, B Adams, D Phung, S Venkatesh, D Gatica-Perez
Proceedings of the 17th ACM international conference on Multimedia, 813-816, 2009
562009
Column networks for collective classification
T Pham, T Tran, D Phung, S Venkatesh
Thirty-First AAAI Conference on Artificial Intelligence, 2017
552017
Ordinal Boltzmann machines for collaborative filtering
T Tran, DQ Phung, S Venkatesh
Arxiv preprint arXiv:1205.2611, 2009
53*2009
MGAN: Training generative adversarial nets with multiple generators
Q Hoang, TD Nguyen, T Le, D Phung
International Conference on Learning Representation (ICLR), 2018
51*2018
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
512015
Stabilized sparse ordinal regression for medical risk stratification
T Tran, D Phung, W Luo, S Venkatesh
Knowledge and Information Systems 43 (3), 555-582, 2015
422015
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Articles 1–20