Dinh Phung
Cited by
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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
Labeled random finite sets and the Bayes multi-target tracking filter
BN Vo, BT Vo, D Phung
IEEE Transaction on Signal Processing, 2014
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
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
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
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
Dual discriminator generative adversarial nets
T Nguyen, T Le, H Vu, D Phung
Advances in neural information processing systems 30, 2017
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
MGAN: Training generative adversarial nets with multiple generators
Q Hoang, TD Nguyen, T Le, D Phung
International Conference on Learning Representation (ICLR), 2018
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
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
An effective spatial-temporal attention based neural network for traffic flow prediction
LNN Do, HL Vu, BQ Vo, Z Liu, D Phung
Transportation research part C: emerging technologies 108, 12-28, 2019
Animal recognition and identification with deep convolutional neural networks for automated wildlife monitoring
H Nguyen, SJ Maclagan, TD Nguyen, T Nguyen, P Flemons, K Andrews, ...
2017 IEEE international conference on data science and advanced Analytics …, 2017
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
Column networks for collective classification
T Pham, T Tran, D Phung, S Venkatesh
Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017
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
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
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
Topic modelling meets deep neural networks: A survey
H Zhao, D Phung, V Huynh, Y Jin, L Du, W Buntine
arXiv preprint arXiv:2103.00498, 2021
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
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Articles 1–20