Truyen Tran

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Svetha VenkateshDeakin Distinguished Professor, Deakin UniversityVerified email at deakin.edu.au
Dinh PhungProfessor, Monash UniversityVerified email at monash.edu
Hoa Khanh DamProfessor in Software Engineering, University of WollongongVerified email at uow.edu.au
Trang PhamSoftware Engineer, GoogleVerified email at google.com
Vuong LeDeakin UniversityVerified email at deakin.edu.au
Sunil GuptaProfessor, Head of AI Optimization and Materials Discovery, Deakin UniversityVerified email at deakin.edu.au
Wei LuoDeakin UniversityVerified email at deakin.edu.au
Aditya GhoseProfessor of Computer Science, University of WollongongVerified email at uow.edu.au
Santu RanaAssociate Professor of Computer Science, Deakin UniversityVerified email at deakin.edu.au
Kien DoApplied Artificial Intelligence Institute (A2I2), Deakin UniversityVerified email at deakin.edu.au
Phuoc NguyenResearch Lecturer, A2I2, Deakin UniversityVerified email at deakin.edu.au
Hung LeResearch Lecturer (Assistant Professor), Deakin UniversityVerified email at deakin.edu.au
Thao Minh LeDeakin UniversityVerified email at deakin.edu.au
John C. GrundyAustralian Laureate Fellow and Professor of Software Engineering, Faculty of IT, Monash UniversityVerified email at monash.edu
Michael BerkDeakin UniversityVerified email at deakin.edu.au
Thin NguyenSenior Research Lecturer, Deakin University, AustraliaVerified email at deakin.edu.au
Morakot Choetkiertikul, Ph.D.Lecture at Faculty of ICT, Mahidol UniversityVerified email at mahidol.ac.th
Chandan KarmakarAssociate Professor, Deakin UniversityVerified email at deakin.edu.au
Tu Dinh NguyenCanvaVerified email at canva.com
Hoang Thanh-TungUniversity of Engineering and Technology, Vietnam National University HanoiVerified email at vnu.edu.vn

Truyen Tran

Professor | Head of AI, Health and Science @ Deakin University

Verified email at deakin.edu.au - Homepage

artificial intelligence AI for health AI for science


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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	811	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	530	2017
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	444*	2017
DeepCare: A deep dynamic memory model for predictive medicine T Pham, T Tran, D Phung, S Venkatesh PAKDD, 30-41, 2016	394	2016
Learning regularity in skeleton trajectories for anomaly detection in videos R Morais, V Le, T Tran, B Saha, M Mansour, S Venkatesh CVPR19, 11988-11996, 2019	343	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	313*	2018
Hierarchical conditional relation networks for video question answering TM Le, V Le, S Venkatesh, T Tran CVPR'20, 2020	299	2020
Catastrophic forgetting and mode collapse in GANs H Thanh-Tung, T Tran IJCNN'20, 1-10, 2020	296	2020
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	260*	2019
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	220	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, 2015	207	2015
Graph transformation policy network for chemical reaction prediction K Do, T Tran, S Venkatesh Proceedings of the 25th ACM SIGKDD International Conference 609, 750-760, 2019	194	2019
Column networks for collective classification T Pham, T Tran, D Phung, S Venkatesh AAAI'17, 2017	191	2017
Explainable software analytics HK Dam, T Tran, A Ghose ICSE'18, 2018	190	2018
Improving generalization and stability of Generative Adversarial Networks H Thanh-Tung, T Tran, S Venkatesh ICLR'19, 2019	157	2019
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	153	2014
A deep language model for software code HK Dam, T Tran, T Pham FSE'16 Workshop on Naturalness of Software (NL+SE), 2016	144	2016
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	115	2014
Dual memory neural computer for asynchronous two-view sequential learning H Le, T Tran, S Venkatesh KDD'18, 2018	112	2018
Towards effective AI-powered agile project management HK Dam, T Tran, J Grundy, A Ghose, Y Kamei ICSE'19, 2019	98	2019

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