T. Tran

Aditya K. Ghose, Truyen Tran, Khanh Hoa Dam, 2018, 2018 IEEE/ACM 40th International Conference on Software Engineering: New Ideas and Emerging Technologies Results (ICSE-NIER).

Preterm Birth Prediction: Stable Selection of Interpretable Rules from High Dimensional Data

Wei Luo, Svetha Venkatesh, Truyen Tran, 2016, MLHC.

Hybrid Generative-Discriminative Models for Inverse Materials Design pdf

Svetha Venkatesh, Truyen Tran, Phuoc Nguyen, 2018, ArXiv.

Erratum to: Preference Relation-based Markov Random Fields for Recommender Systems

Gang Li, T. Tran, Yuan Jiang, 2017, Machine Learning.

An evaluation of randomized machine learning methods for redundant data: Predicting short and medium-term suicide risk from administrative records and risk assessments pdf

Svetha Venkatesh, Truyen Tran, Dinh Q. Phung, 2016, ArXiv.

Towards Effective and Robust Neural Trojan Defenses via Input Filtering

S. Rana, T. Tran, Hung Le, 2022, ArXiv.

Resset: A Recurrent Model for Sequence of Sets with Applications to Electronic Medical Records

S. Venkatesh, Phuoc Nguyen, T. Tran, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Neural Reasoning for Chemical-Chemical Interaction

S. Venkatesh, T. Tran, Trang Pham, 2018 .

Web search activity data accurately predict population chronic disease risk in the USA

Wei Luo, Svetha Venkatesh, Truyen Tran, 2015, Journal of Epidemiology & Community Health.

Screening for post 32-week preterm birth risk: how helpful is routine perinatal data collection?

Svetha Venkatesh, Truyen Tran, Dinh Phung, 2016, Heliyon.

DeepTRIAGE: interpretable and individualised biomarker scores using attention mechanism for the classification of breast cancer sub-types

Svetha Venkatesh, Truyen Tran, Adham Beykikhoshk, 2019, bioRxiv.

A Spatio-Temporal Attention-Based Model for Infant Movement Assessment From Videos

Svetha Venkatesh, Truyen Tran, Binh Nguyen-Thai, 2021, IEEE Journal of Biomedical and Health Informatics.

Automatically recommending components for issue reports using deep learning

Aditya K. Ghose, Morakot Choetkiertikul, Truyen Tran, 2021, Empirical Software Engineering.

Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation

S. Rana, T. Tran, D. Nguyen, 2022, NeurIPS.

G ENERATIVE P SEUDO -I NVERSE M EMORY

T. Tran, Hung Le, S. Venkatesh, 2022 .

Machine Learning-Aided Exploration of Ultrahard Materials

Phuoc Nguyen, T. Tran, T. Walsh, 2022, The Journal of Physical Chemistry C.

TATES COOPERATIVE REINFORCEMENT LEARNING

S. Venkatesh, T. Tran, D. Nguyen, 2020 .

Functional Indirection Neural Estimator for Better Out-of-distribution Generalization

T. Tran, Hung Le, Man Ngo, 2022, NeurIPS.

Variational Hyper-encoding Networks

S. Rana, S. Venkatesh, Phuoc Nguyen, 2020, ECML/PKDD.

Energy-based anomaly detection for mixed data

T. Tran, Kien Do, S. Venkatesh, 2018, Knowledge and Information Systems.

Tree-based iterated local search for Markov random fields with applications in image analysis

Dinh Q. Phung, T. Tran, S. Venkatesh, 2014, Journal of Heuristics.

Video Dialog as Conversation about Objects Living in Space-Time

Tu Minh Phuong, Thao Minh Le, T. Tran, 2022, ECCV.

Memory-Augmented Theory of Mind Network

Phuoc Nguyen, T. Tran, Hung Le, 2023, ArXiv.

Deep in the Bowel: Highly Interpretable Neural Encoder-Decoder Networks Predict Gut Metabolites from Gut Microbiome

Truyen Tran, Svetha Venkatesh, Thomas P. Quinn, 2019, BMC Genomics.

Statistical Latent Space Approach for Mixed Data Modelling and Applications pdf

Svetha Venkatesh, Truyen Tran, Tu Dinh Nguyen, 2017, ArXiv.

Deepr: A Convolutional Net for Medical Records pdf

Nilmini Wickramasinghe, Truyen Tran, Phuoc Nguyen, 2016, ArXiv.

Counterfactual Explanation with Multi-Agent Reinforcement Learning for Drug Target Prediction pdf

Truyen Tran, Thin Nguyen, Thomas P Quinn, 2021, ArXiv.

2 5 M ay 2 01 9 Neural Stored-programMemory

S. Venkatesh, T. Tran, Hung Le, 2019 .

Neural Choice by Elimination via Highway Networks

Svetha Venkatesh, Truyen Tran, Dinh Q. Phung, 2016, PAKDD Workshops.

Choice by Elimination via Deep Neural Networks pdf

Svetha Venkatesh, Truyen Tran, Dinh Q. Phung, 2016, ArXiv.

An integrated framework for suicide risk prediction

Wei Luo, Svetha Venkatesh, Truyen Tran, 2013, KDD.

Thurstonian Boltzmann Machines: Learning from Multiple Inequalities pdf

Svetha Venkatesh, Truyen Tran, Dinh Q. Phung, 2013, ICML.

Thurstonian Boltzmann Machines : Learning from Multiple Inequalities Supplementary Material

Dinh Q. Phung, S. Venkatesh, T. Tran, 2013 .

A Sequential Decision Approach to Ordinal Preferences in Recommender Systems

Svetha Venkatesh, Truyen Tran, Dinh Q. Phung, 2012, AAAI.

Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis pdf

Svetha Venkatesh, Truyen Tran, Dinh Q. Phung, 2014, ACML.

Predicting Delivery Capability in Iterative Software Development

John Grundy, Morakot Choetkiertikul, Hoa Khanh Dam, 2018, IEEE Transactions on Software Engineering.

Predicting the delay of issues with due dates in software projects

Aditya K. Ghose, Morakot Choetkiertikul, Truyen Tran, 2017, Empirical Software Engineering.

Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View

Wei Luo, John Yearwood, Tu Bao Ho, 2016, Journal of medical Internet research.

Preterm Birth Prediction: Deriving Stable and Interpretable Rules from High Dimensional Data

Wei Luo, Truyen Tran, Svetha Venkatesh, 2016, 1607.08310.

Embedded Restricted Boltzmann Machines for fusion of mixed data types and applications in social measurements analysis

Svetha Venkatesh, Truyen Tran, Dinh Q. Phung, 2012, 2012 15th International Conference on Information Fusion.

Learning to discover medicines

T. Tran, Thin Nguyen, T. Nguyen, 2022, International Journal of Data Science and Analytics.

Mitigating cold-start problems in drug-target affinity prediction with interaction knowledge transferring

T. Tran, Thin Nguyen, T. Nguyen, 2022, Briefings Bioinform..

Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)

Svetha Venkatesh, Truyen Tran, Tu Dinh Nguyen, 2015, J. Biomed. Informatics.

DeepTRIAGE: interpretable and individualised biomarker scores using attention mechanism for the classification of breast cancer sub-types

Truyen Tran, Samuel C. Lee, Svetha Venkatesh, 2019, BMC Medical Genomics.

Mixed-Variate Restricted Boltzmann Machines pdf

Svetha Venkatesh, Truyen Tran, Dinh Q. Phung, 2014, ACML.

Model-Based Episodic Memory Induces Dynamic Hybrid Controls pdf

Thommen George Karimpanal, Svetha Venkatesh, Majid Abdolshah, 2021, NeurIPS.

Modelling human preferences for ranking and collaborative filtering: a probabilistic ordered partition approach

Svetha Venkatesh, Truyen Tran, Dinh Q. Phung, 2016, Knowledge and Information Systems.

Probabilistic Models over Ordered Partitions with Applications in Document Ranking and Collaborative Filtering

Svetha Venkatesh, Truyen Tran, Dinh Q. Phung, 2011, SDM.

Hierarchical Object-oriented Spatio-Temporal Reasoning for Video Question Answering

Truyen Tran, Vuong Le, Thao Minh Le, 2021, IJCAI.

Theory and Evaluation Metrics for Learning Disentangled Representations pdf

Truyen Tran, Kien Do, T. Tran, 2019, ICLR.

Forecasting Daily Patient Outflow From a Ward Having No Real-Time Clinical Data

Wei Luo, Truyen Tran, Svetha Venkatesh, 2016, JMIR medical informatics.

Catastrophic forgetting and mode collapse in GANs

Truyen Tran, Hoang Thanh-Tung, T. Tran, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Learning From Ordered Sets and Applications in Collaborative Ranking pdf

Svetha Venkatesh, Truyen Tran, Dinh Q. Phung, 2014, ACML.

Towards Effective and Robust Neural Trojan Defenses via Input Filtering

S. Rana, T. Tran, Hung Le, 2022, ECCV.

Graph Transformation Policy Network for Chemical Reaction Prediction

Svetha Venkatesh, Truyen Tran, Kien Do, 2018, KDD.

Tree-based iterated local search for Markov random fields with applications in image analysis

Svetha Venkatesh, Truyen Tran, Dinh Q. Phung, 2014, J. Heuristics.

Predicting Risk of Suicide Attempt Using History of Physical Illnesses From Electronic Medical Records

Svetha Venkatesh, Truyen Tran, Chandan Karmakar, 2016, JMIR mental health.

Automatic Feature Learning for Predicting Vulnerable Software Components

Hoa Khanh Dam, Truyen Tran, Aditya Ghose, 2021, IEEE Transactions on Software Engineering.

Learning Theory of Mind via Dynamic Traits Attribution

S. Venkatesh, Phuoc Nguyen, T. Tran, 2022, AAMAS.

Hierarchical Conditional Relation Networks for Video Question Answering

Truyen Tran, Svetha Venkatesh, Vuong Le, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

A deep tree-based model for software defect prediction pdf

Aditya K. Ghose, John Grundy, Truyen Tran, 2018, ArXiv.

Towards Effective AI-Powered Agile Project Management

Aditya K. Ghose, John C. Grundy, Truyen Tran, 2018, 2019 IEEE/ACM 41st International Conference on Software Engineering: New Ideas and Emerging Results (ICSE-NIER).

Graph Memory Networks for Molecular Activity Prediction

Svetha Venkatesh, Truyen Tran, Trang Pham, 2018, 2018 24th International Conference on Pattern Recognition (ICPR).

Dual Memory Neural Computer for Asynchronous Two-view Sequential Learning

Svetha Venkatesh, Truyen Tran, Hung Le, 2018, KDD.

Precision psychiatry with immunological and cognitive biomarkers: a multi-domain prediction for the diagnosis of bipolar disorder or schizophrenia using machine learning

M. Leboyer, R. Yolken, S. Venkatesh, 2020, Translational Psychiatry.

Learning to Abstract and Predict Human Actions pdf

Truyen Tran, Svetha Venkatesh, Vuong Le, 2020, BMVC.

Goal-driven Long-Term Trajectory Prediction pdf

Truyen Tran, Hung Tran, Vuong Le, 2020, 2021 IEEE Winter Conference on Applications of Computer Vision (WACV).

Knowledge Distillation with Distribution Mismatch

Santu Rana, Sunil Gupta, Dang Nguyen, 2021, ECML/PKDD.

Learning Asynchronous and Sparse Human-Object Interaction in Videos

Svetha Venkatesh, Truyen Tran, Vuong Le, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos

Svetha Venkatesh, Truyen Tran, Moussa Reda Mansour, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Knowledge Graph Embedding with Multiple Relation Projections

Svetha Venkatesh, Truyen Tran, Kien Do, 2018, 2018 24th International Conference on Pattern Recognition (ICPR).

GEFA: Early Fusion Approach in Drug-Target Affinity Prediction pdf

Truyen Tran, Tri Minh Nguyen, Thin Nguyen, 2020, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

One Size Fits Many: Column Bundle for Multi-X Learning pdf

Svetha Venkatesh, Truyen Tran, Trang Pham, 2017, ArXiv.

Predicting Delays in Software Projects Using Networked Classification (T)

Aditya K. Ghose, Morakot Choetkiertikul, Truyen Tran, 2015, 2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE).

Energy-based anomaly detection for mixed data

Svetha Venkatesh, Truyen Tran, Kien Do, 2018, Knowledge and Information Systems.

Multilevel Anomaly Detection for Mixed Data pdf

Svetha Venkatesh, Truyen Tran, Kien Do, 2016, ArXiv.

Toward a Generalization Metric for Deep Generative Models pdf

Truyen Tran, Hoang Thanh-Tung, T. Tran, 2020, ArXiv.

Improving Generalization and Stability of Generative Adversarial Networks pdf

Truyen Tran, Svetha Venkatesh, Hoang Thanh-Tung, 2019, ICLR.

Tensor-Variate Restricted Boltzmann Machines

Svetha Venkatesh, Truyen Tran, Tu Dinh Nguyen, 2015, AAAI.

Personalized Annotation-based Networks (PAN) for the Prediction of Breast Cancer Relapse

Truyen Tran, Thuc Duy Le, Samuel C. Lee, 2019, bioRxiv.

A Deep Learning Model for Estimating Story Points

Tim Menzies, Morakot Choetkiertikul, Hoa Khanh Dam, 2016, IEEE Transactions on Software Engineering.

Consistency of the Health of the Nation Outcome Scales (HoNOS) at inpatient-to-community transition

S. Venkatesh, T. Tran, Dinh Phung, 2016, BMJ Open.

Unsupervised Anomaly Detection on Temporal Multiway Data

Truyen Tran, Kien Do, Phuoc Nguyen, 2020, 2020 IEEE Symposium Series on Computational Intelligence (SSCI).

Neural Stored-program Memory pdf

Truyen Tran, Hung Le, Svetha Venkatesh, 2019, ICLR.

Hyper-community detection in the blogosphere

Svetha Venkatesh, Truyen Tran, Brett Adams, 2010, WSM@MM.

A framework for feature extraction from hospital medical data with applications in risk prediction

Wei Luo, Svetha Venkatesh, Truyen Tran, 2014, BMC Bioinformatics.

DeepCare: A Deep Dynamic Memory Model for Predictive Medicine

Svetha Venkatesh, Truyen Tran, Dinh Q. Phung, 2016, PAKDD.

Permutation Models for Collaborative Ranking pdf

Svetha Venkatesh, Truyen Tran, S. Venkatesh, 2014, ArXiv.

Dynamic Language Binding in Relational Visual Reasoning

Thao Minh Le, S. Venkatesh, T. Tran, 2020, IJCAI.

Classification and Pattern Discovery of Mood in Weblogs

Svetha Venkatesh, Truyen Tran, Brett Adams, 2010, PAKDD.

iPoll: Automatic Polling Using Online Search

Wei Luo, Svetha Venkatesh, Truyen Tran, 2014, WISE.

Stabilized sparse ordinal regression for medical risk stratification

Wei Luo, Svetha Venkatesh, Truyen Tran, 2014, Knowledge and Information Systems.

On catastrophic forgetting and mode collapse in Generative Adversarial Networks pdf

Truyen Tran, Svetha Venkatesh, Hoang Thanh-Tung, 2018, ArXiv.

Effect of pre-loading on chloride diffusion in concrete

T. Tran, H. Ranaivomanana, A. Khelidj, 2018, Journal of Asian Concrete Federation.

Learning Boltzmann Distance Metric for Face Recognition

Svetha Venkatesh, Truyen Tran, Dinh Q. Phung, 2012, 2012 IEEE International Conference on Multimedia and Expo.

Forecasting Patient Outflow from Wards having No Real-Time Clinical Data

Wei Luo, Svetha Venkatesh, Truyen Tran, 2016, 2016 IEEE International Conference on Healthcare Informatics (ICHI).

Attentional multilabel learning over graphs: a message passing approach

Svetha Venkatesh, Truyen Tran, Kien Do, 2018, Machine Learning.

On catastrophic forgetting in Generative Adversarial Networks

Truyen Tran, Hoang Thanh-Tung, T. Tran, 2018 .

Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning

Truyen Tran, Phuoc Nguyen, Svetha Venkatesh, 2020, ACML.

Graph Classification via Deep Learning with Virtual Nodes pdf

Svetha Venkatesh, Truyen Tran, Khanh Hoa Dam, 2017, ArXiv.

Relational dynamic memory networks pdf

Svetha Venkatesh, Truyen Tran, Trang Pham, 2018, ArXiv.

Variational Memory Encoder-Decoder

Svetha Venkatesh, Truyen Tran, Hung Le, 2018, NeurIPS.

Faster training of very deep networks via p-norm gates

Svetha Venkatesh, Truyen Tran, Dinh Q. Phung, 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).

Self-Attentive Associative Memory

S. Venkatesh, T. Tran, Hung Le, 2020, ICML.

I MPROVING O UT - OF - DISTRIBUTION G ENERALIZATION WITH I NDIRECTION R EPRESENTATIONS

T. Tran, Hung Le, Kha Pham, 2023 .

Global optimization using Lévy flights pdf

Trung Thanh Nguyen, Truyen Tran, Hoang Linh Nguyen, 2014, ArXiv.

HyperVAE: A Minimum Description Length Variational Hyper-Encoding Network pdf

Truyen Tran, Phuoc Nguyen, Santu Rana, 2020, ArXiv.

Automatic feature learning for vulnerability prediction pdf

Aditya K. Ghose, John Grundy, Truyen Tran, 2017, ArXiv.

Lessons Learned from Using a Deep Tree-Based Model for Software Defect Prediction in Practice

Aditya K. Ghose, John C. Grundy, Truyen Tran, 2019, 2019 IEEE/ACM 16th International Conference on Mining Software Repositories (MSR).

Object-Centric Representation Learning for Video Question Answering

Thao Minh Le, Long Hoang Dang, T. Tran, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Resset: A Recurrent Model for Sequence of Sets with Applications to Electronic Medical Records

S. Venkatesh, Phuoc Nguyen, T. Tran, 2018, IJCNN.

Dual Control Memory Augmented Neural Networks for Treatment Recommendations

Svetha Venkatesh, Truyen Tran, Hung Le, 2018, PAKDD.

Fast Conditional Network Compression Using Bayesian HyperNetworks

Santu Rana, Sunil Gupta, Dang Nguyen, 2022, ECML/PKDD.

Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization pdf

Svetha Venkatesh, Truyen Tran, Kien Do, 2020, AAAI.

Learning to Remember More with Less Memorization pdf

Svetha Venkatesh, Truyen Tran, Hung Le, 2019, ICLR.

Poster: Predicting Components for Issue Reports Using Deep Learning with Information Retrieval

Aditya K. Ghose, Morakot Choetkiertikul, Truyen Tran, 2018, 2018 IEEE/ACM 40th International Conference on Software Engineering: Companion (ICSE-Companion).

Committee machine that votes for similarity between materials

Truyen Tran, Keisuke Takahashi, Hieu-Chi Dam, 2018, IUCrJ.

Learning to Reason with Relational Video Representation for Question Answering pdf

Svetha Venkatesh, Truyen Tran, Vuong Le, 2019, ArXiv.

LaGR-SEQ: Language-Guided Reinforcement Learning with Sample-Efficient Querying

S. Gupta, T. Tran, S. Venkatesh, 2023, ArXiv.

I MPROVING G ENERALIZATION AND S TABILITY OF G ENERATIVE A DVERSARIAL N ETWORKS

T. Tran, Hoang Thanh-Tung, S. Venkatesh, 2022 .

Preference Relation-based Markov Random Fields for Recommender Systems

Yuan Jiang, Truyen Tran, Gang Li, 2017, Machine Learning.

Erratum to: Preference Relation-based Markov Random Fields for Recommender Systems

Gang Li, T. Tran, Yuan Jiang, 2017, Machine Learning.