Truyen Tran

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	All	Since 2016
Citations	3014	2676
h-index	28	26
i10-index	64	55

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Co-authors

Svetha VenkateshProfessor of Computer Science, Deakin UniversityVerified email at deakin.edu.au
Dinh PhungProfessor, Monash UniversityVerified email at monash.edu
Wei LuoDeakin UniversityVerified email at deakin.edu.au
Trang PhamSoftware Engineer, GoogleVerified email at google.com
Hoa Khanh DamAssociate Professor in Software Engineering, University of WollongongVerified email at uow.edu.au
Aditya GhoseProfessor of Computer Science, University of WollongongVerified email at uow.edu.au
Sunil GuptaAssociate Professor, Deakin UniversityVerified email at deakin.edu.au
Santu RanaAssociate Professor of Computer Science, Deakin UniversityVerified email at deakin.edu.au
Phuoc NguyenAssociate research fellow, Deakin UniversityVerified email at deakin.edu.au
Michael BerkDeakin UniversityVerified email at deakin.edu.au
Tu Dinh NguyenLead Research Scientist, Trusting SocialVerified email at trustingsocial.com
John GrundyAustralian Laureate Fellow and Professor of Software Engineering, Faculty of IT, Monash UniversityVerified email at monash.edu
Kien DoDeakin UniversityVerified email at deakin.edu.au
Morakot Choetkiertikul, Ph.D.Lecture at Faculty of ICT, Mahidol UniversityVerified email at mahidol.ac.th
Thin NguyenSenior Research Fellow, Deakin University, AustraliaVerified email at deakin.edu.au
Hung BuiResearch Scientist, Google DeepMindVerified email at google.com
Hung LeDeakin UniversityVerified email at deakin.edu.au
Vuong LeDeakin UniversityVerified email at deakin.edu.au
Chandan KarmakarLecturer of Computer Science, Deakin UniversityVerified email at deakin.edu.au
Shivapratap GopakumarDeakin UniversityVerified email at deakin.edu.au

Truyen Tran

Associate Professor, Applied AI Institute, Deakin University

Verified email at deakin.edu.au - Homepage

artificial intelligence machine learning computational biomedicine computer vision


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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), 2016	213	2016
Deepr: 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, 2017	207*	2017
DeepCare: A deep dynamic memory model for predictive medicine T Pham, T Tran, D Phung, S Venkatesh PAKDD 6, 26094, 2016	196	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	184	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, 2015	116	2015
Column networks for collective classification T Pham, T Tran, D Phung, S Venkatesh AAAI'17, 2017	110	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 (ECR Best paper awarded by CRESP), 2014	97	2014
Nonnegative shared subspace learning and its application to social media retrieval SK Gupta, D Phung, B Adams, T Tran, S Venkatesh KDD'10, 1169-1178, 2010	89	2010
Ordinal Boltzmann machines for collaborative filtering TT Truyen, DQ Phung, S Venkatesh UAI'09 (Best paper runner up), 548-556, 2009	68	2009
Lessons learned from using a deep tree-based model for software defect prediction in practice HK Dam, T Pham, SW Ng, T Tran, J Grundy, A Ghose, T Kim, CJ Kim MSR'19, 2019	67*	2019
Automatic feature learning for predicting vulnerable software components HK Dam, T Tran, T Pham, SW Ng, J Grundy, A Ghose IEEE Transactions on Software Engineering, 2018	67*	2018
Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry S Gupta, T Tran, W Luo, D Phung, RL Kennedy, A Broad, D Campbell, ... BMJ Open, 2014	63	2014
A deep learning model for estimating story points M Choetkiertikul, HK Dam, T Tran, T Pham, A Ghose, T Menzies IEEE Transactions on Software Engineering, DOI:10.1109/TSE.2018.2792473, 2018	61	2018
Improving generalization and stability of Generative Adversarial Networks H Thanh-Tung, T Tran, S Venkatesh ICLR'19, 2019	58	2019
A deep language model for software code HK Dam, T Tran, T Pham FSE'16 Workshop on Naturalness of Software (NL+SE), 2016	56	2016
Stabilized sparse ordinal regression for medical risk stratification T Tran, D Phung, W Luo, S Venkatesh Knowledge and Information Systems, 2015	52	2015
Explainable software analytics HK Dam, T Tran, A Ghose ICSE'18, 2018	50	2018
Hierarchical semi-Markov conditional random fields for recursive sequential data T Tran, D Phung, H Bui, S Venkatesh NIPS'08, 2008	44	2008
Mixed-variate restricted Boltzmann machines T Tran, D Phung, S Venkatesh ACML'11, 2011	42	2011
Learning regularity in skeleton trajectories for anomaly detection in videos R Morais, V Le, B Saha, T Tran, MR Mansour, S Venkatesh CVPR'19, 2019	40	2019

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