Truyen Tran

Orcid: 0000-0001-6531-8907

Affiliations:
  • Deakin University, Center for Pattern Recognition and Data Analyticss (PRaDA), Geelong, Australia
  • Curtin University of Technology, Department of Computing, Perth, Australia (PhD 2008)


According to our database1, Truyen Tran authored at least 155 papers between 2006 and 2024.

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Bibliography

2024
Revisiting the Dataset Bias Problem from a Statistical Perspective.
CoRR, 2024

Root Cause Explanation of Outliers under Noisy Mechanisms.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Balanced Q-learning: Combining the influence of optimistic and pessimistic targets.
Artif. Intell., December, 2023

Robust and Interpretable General Movement Assessment Using Fidgety Movement Detection.
IEEE J. Biomed. Health Informatics, October, 2023

Learning to discover medicines.
Int. J. Data Sci. Anal., September, 2023

Explaining Black Box Drug Target Prediction Through Model Agnostic Counterfactual Samples.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023

LaGR-SEQ: Language-Guided Reinforcement Learning with Sample-Efficient Querying.
CoRR, 2023

Guiding Visual Question Answering with Attention Priors.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Vision: Requirements Engineering for Software Development in Aged Care.
Proceedings of the 31st IEEE International Requirements Engineering Conference, RE 2023, 2023

Social Motivation for Modelling Other Agents under Partial Observability in Decentralised Training.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Improving Out-of-distribution Generalization with Indirection Representations.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Persistent-Transient Duality: A Multi-mechanism Approach for Modeling Human-Object Interaction.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Memory-Augmented Theory of Mind Network.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
GEFA: Early Fusion Approach in Drug-Target Affinity Prediction.
IEEE ACM Trans. Comput. Biol. Bioinform., 2022

Mitigating cold-start problems in drug-target affinity prediction with interaction knowledge transferring.
Briefings Bioinform., 2022

Functional Indirection Neural Estimator for Better Out-of-distribution Generalization.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Momentum Adversarial Distillation: Handling Large Distribution Shifts in Data-Free Knowledge Distillation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Generative Pseudo-Inverse Memory.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Video Dialog as Conversation About Objects Living in Space-Time.
Proceedings of the Computer Vision - ECCV 2022, 2022

Towards Effective and Robust Neural Trojan Defenses via Input Filtering.
Proceedings of the Computer Vision - ECCV 2022, 2022

Persistent-Transient Duality in Human Behavior Modeling.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

Learning to Transfer Role Assignment Across Team Sizes.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

Learning Theory of Mind via Dynamic Traits Attribution.
Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, 2022

2021
Automatic Feature Learning for Predicting Vulnerable Software Components.
IEEE Trans. Software Eng., 2021

A Spatio-Temporal Attention-Based Model for Infant Movement Assessment From Videos.
IEEE J. Biomed. Health Informatics, 2021

PAN: Personalized Annotation-Based Networks for the Prediction of Breast Cancer Relapse.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021

Hierarchical Conditional Relation Networks for Multimodal Video Question Answering.
Int. J. Comput. Vis., 2021

Automatically recommending components for issue reports using deep learning.
Empir. Softw. Eng., 2021

Counterfactual Explanation with Multi-Agent Reinforcement Learning for Drug Target Prediction.
CoRR, 2021

Goal-driven Long-Term Trajectory Prediction.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Fast Conditional Network Compression Using Bayesian HyperNetworks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Variational Hyper-encoding Networks.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Knowledge Distillation with Distribution Mismatch.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Model-Based Episodic Memory Induces Dynamic Hybrid Controls.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

From Deep Learning to Deep Reasoning.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Object-Centric Representation Learning for Video Question Answering.
Proceedings of the International Joint Conference on Neural Networks, 2021

Hierarchical Object-oriented Spatio-Temporal Reasoning for Video Question Answering.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

DeepProcess: Supporting Business Process Execution Using a MANN-Based Recommender System.
Proceedings of the Service-Oriented Computing - 19th International Conference, 2021

Clustering by Maximizing Mutual Information Across Views.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Learning Asynchronous and Sparse Human-Object Interaction in Videos.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Logically Consistent Loss for Visual Question Answering.
CoRR, 2020

Toward a Generalization Metric for Deep Generative Models.
CoRR, 2020

HyperVAE: A Minimum Description Length Variational Hyper-Encoding Network.
CoRR, 2020

Unsupervised Anomaly Detection on Temporal Multiway Data.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Catastrophic forgetting and mode collapse in GANs.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Neural Reasoning, Fast and Slow, for Video Question Answering.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Dynamic Language Binding in Relational Visual Reasoning.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Self-Attentive Associative Memory.
Proceedings of the 37th International Conference on Machine Learning, 2020

Neural Stored-program Memory.
Proceedings of the 8th International Conference on Learning Representations, 2020

Theory and Evaluation Metrics for Learning Disentangled Representations.
Proceedings of the 8th International Conference on Learning Representations, 2020

Hierarchical Conditional Relation Networks for Video Question Answering.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Learning to Abstract and Predict Human Actions.
Proceedings of the 31st British Machine Vision Conference 2020, 2020

Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning.
Proceedings of The 12th Asian Conference on Machine Learning, 2020

2019
A Deep Learning Model for Estimating Story Points.
IEEE Trans. Software Eng., 2019

Attentional multilabel learning over graphs: a message passing approach.
Mach. Learn., 2019

Learning to Reason with Relational Video Representation for Question Answering.
CoRR, 2019

Incomplete Conditional Density Estimation for Fast Materials Discovery.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Lessons learned from using a deep tree-based model for software defect prediction in practice.
Proceedings of the 16th International Conference on Mining Software Repositories, 2019

Graph Transformation Policy Network for Chemical Reaction Prediction.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Towards effective AI-powered agile project management.
Proceedings of the 41st International Conference on Software Engineering: New Ideas and Emerging Results, 2019

Improving Generalization and Stability of Generative Adversarial Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

Learning to Remember More with Less Memorization.
Proceedings of the 7th International Conference on Learning Representations, 2019

Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
Predicting Delivery Capability in Iterative Software Development.
IEEE Trans. Software Eng., 2018

Energy-based anomaly detection for mixed data.
Knowl. Inf. Syst., 2018

Hybrid Generative-Discriminative Models for Inverse Materials Design.
CoRR, 2018

Relational dynamic memory networks.
CoRR, 2018

On catastrophic forgetting and mode collapse in Generative Adversarial Networks.
CoRR, 2018

Memory-Augmented Neural Networks for Predictive Process Analytics.
CoRR, 2018

A deep tree-based model for software defect prediction.
CoRR, 2018

Dual Control Memory Augmented Neural Networks for Treatment Recommendations.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Variational Memory Encoder-Decoder.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Dual Memory Neural Computer for Asynchronous Two-view Sequential Learning.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Resset: A Recurrent Model for Sequence of Sets with Applications to Electronic Medical Records.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Explainable software analytics.
Proceedings of the 40th International Conference on Software Engineering: New Ideas and Emerging Results, 2018

Predicting components for issue reports using deep learning with information retrieval.
Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings, 2018

Graph Memory Networks for Molecular Activity Prediction.
Proceedings of the 24th International Conference on Pattern Recognition, 2018

Knowledge Graph Embedding with Multiple Relation Projections.
Proceedings of the 24th International Conference on Pattern Recognition, 2018

2017
<tt>Deepr</tt>: A Convolutional Net for Medical Records.
IEEE J. Biomed. Health Informatics, 2017

Erratum to: Preference Relation-based Markov Random Fields for Recommender Systems.
Mach. Learn., 2017

Preference Relation-based Markov Random Fields for Recommender Systems.
Mach. Learn., 2017

Predicting healthcare trajectories from medical records: A deep learning approach.
J. Biomed. Informatics, 2017

Predicting the delay of issues with due dates in software projects.
Empir. Softw. Eng., 2017

Finding Algebraic Structure of Care in Time: A Deep Learning Approach.
CoRR, 2017

Nonnegative Restricted Boltzmann Machines for Parts-based Representations Discovery and Predictive Model Stabilization.
CoRR, 2017

Statistical Latent Space Approach for Mixed Data Modelling and Applications.
CoRR, 2017

Graph Classification via Deep Learning with Virtual Nodes.
CoRR, 2017

Automatic feature learning for vulnerability prediction.
CoRR, 2017

One Size Fits Many: Column Bundle for Multi-X Learning.
CoRR, 2017

Matrix-centric Neural Networks.
CoRR, 2017

Hierarchical semi-Markov conditional random fields for deep recursive sequential data.
Artif. Intell., 2017

Deep Learning to Attend to Risk in ICU.
Proceedings of the 2nd International Workshop on Knowledge Discovery in Healthcare Data Co-located with the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), 2017

Column Networks for Collective Classification.
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016
Modelling human preferences for ranking and collaborative filtering: a probabilistic ordered partition approach.
Knowl. Inf. Syst., 2016

Collaborative filtering via sparse Markov random fields.
Inf. Sci., 2016

Graph-induced restricted Boltzmann machines for document modeling.
Inf. Sci., 2016

Learning deep representation of multityped objects and tasks.
CoRR, 2016

Choice by Elimination via Deep Neural Networks.
CoRR, 2016

Deepr: A Convolutional Net for Medical Records.
CoRR, 2016

An evaluation of randomized machine learning methods for redundant data: Predicting short and medium-term suicide risk from administrative records and risk assessments.
CoRR, 2016

Multilevel Anomaly Detection for Mixed Data.
CoRR, 2016

A deep language model for software code.
CoRR, 2016

DeepSoft: a vision for a deep model of software.
Proceedings of the 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering, 2016

Neural Choice by Elimination via Highway Networks.
Proceedings of the Trends and Applications in Knowledge Discovery and Data Mining, 2016

DeepCare: A Deep Dynamic Memory Model for Predictive Medicine.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2016

Preterm Birth Prediction: Stable Selection of Interpretable Rules from High Dimensional Data.
Proceedings of the 1st Machine Learning in Health Care, 2016

Faster training of very deep networks via p-norm gates.
Proceedings of the 23rd International Conference on Pattern Recognition, 2016

Forecasting Patient Outflow from Wards having No Real-Time Clinical Data.
Proceedings of the 2016 IEEE International Conference on Healthcare Informatics, 2016

Stabilizing Linear Prediction Models Using Autoencoder.
Proceedings of the Advanced Data Mining and Applications - 12th International Conference, 2016

Outlier Detection on Mixed-Type Data: An Energy-Based Approach.
Proceedings of the Advanced Data Mining and Applications - 12th International Conference, 2016

2015
Stabilizing High-Dimensional Prediction Models Using Feature Graphs.
IEEE J. Biomed. Health Informatics, 2015

Stabilized sparse ordinal regression for medical risk stratification.
Knowl. Inf. Syst., 2015

Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM).
J. Biomed. Informatics, 2015

Tree-based iterated local search for Markov random fields with applications in image analysis.
J. Heuristics, 2015

Stabilizing Sparse Cox Model Using Statistic and Semantic Structures in Electronic Medical Records.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015

Characterization and Prediction of Issue-Related Risks in Software Projects.
Proceedings of the 12th IEEE/ACM Working Conference on Mining Software Repositories, 2015

Predicting Delays in Software Projects Using Networked Classification (T).
Proceedings of the 30th IEEE/ACM International Conference on Automated Software Engineering, 2015

Who Will Answer My Question on Stack Overflow?
Proceedings of the 24th Australasian Software Engineering Conference, 2015

Tensor-Variate Restricted Boltzmann Machines.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Permutation Models for Collaborative Ranking.
CoRR, 2014

MCMC for Hierarchical Semi-Markov Conditional Random Fields.
CoRR, 2014

Learning Structured Outputs from Partial Labels using Forest Ensemble.
CoRR, 2014

Learning Rank Functionals: An Empirical Study.
CoRR, 2014

Global optimization using Lévy flights.
CoRR, 2014

Human Activity Learning and Segmentation using Partially Hidden Discriminative Models.
CoRR, 2014

Boosted Markov Networks for Activity Recognition.
CoRR, 2014

Stabilizing Sparse Cox Model using Clinical Structures in Electronic Medical Records.
CoRR, 2014

A framework for feature extraction from hospital medical data with applications in risk prediction.
BMC Bioinform., 2014

iPoll: Automatic Polling Using Online Search.
Proceedings of the Web Information Systems Engineering - WISE 2014, 2014

Ordinal Random Fields for Recommender Systems.
Proceedings of the Sixth Asian Conference on Machine Learning, 2014

2013
Latent Patient Profile Modelling and Applications with Mixed-Variate Restricted Boltzmann Machine.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2013

An integrated framework for suicide risk prediction.
Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013

Thurstonian Boltzmann Machines: Learning from Multiple Inequalities.
Proceedings of the 30th International Conference on Machine Learning, 2013

Learning sparse latent representation and distance metric for image retrieval.
Proceedings of the 2013 IEEE International Conference on Multimedia and Expo, 2013

Learning Parts-based Representations with Nonnegative Restricted Boltzmann Machine.
Proceedings of the Asian Conference on Machine Learning, 2013

2012
Learning From Ordered Sets and Applications in Collaborative Ranking.
Proceedings of the 4th Asian Conference on Machine Learning, 2012

Cumulative Restricted Boltzmann Machines for Ordinal Matrix Data Analysis.
Proceedings of the 4th Asian Conference on Machine Learning, 2012

ConeRANK: Ranking as Learning Generalized Inequalities
CoRR, 2012

Learning Boltzmann Distance Metric for Face Recognition.
Proceedings of the 2012 IEEE International Conference on Multimedia and Expo, 2012

Embedded Restricted Boltzmann Machines for fusion of mixed data types and applications in social measurements analysis.
Proceedings of the 15th International Conference on Information Fusion, 2012

A Sequential Decision Approach to Ordinal Preferences in Recommender Systems.
Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011
Mixed-Variate Restricted Boltzmann Machines.
Proceedings of the 3rd Asian Conference on Machine Learning, 2011

Probabilistic Models over Ordered Partitions with Applications in Document Ranking and Collaborative Filtering.
Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

2010
Probabilistic Models over Ordered Partitions with Application in Learning to Rank
CoRR, 2010

Classification and Pattern Discovery of Mood in Weblogs.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2010

Hyper-community detection in the blogosphere.
Proceedings of second ACM SIGMM workshop on Social media, 2010

Nonnegative shared subspace learning and its application to social media retrieval.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

2009
Ordinal Boltzmann Machines for Collaborative Filtering.
Proceedings of the UAI 2009, 2009

2008
Constrained Sequence Classification for Lexical Disambiguation.
Proceedings of the PRICAI 2008: Trends in Artificial Intelligence, 2008

Learning Discriminative Sequence Models from Partially Labelled Data for Activity Recognition.
Proceedings of the PRICAI 2008: Trends in Artificial Intelligence, 2008

Hierarchical Semi-Markov Conditional Random Fields for Recursive Sequential Data.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007
Preference Networks: Probabilistic Models for Recommendation Systems.
Proceedings of the Data Mining and Analytics 2007, 2007

2006
AdaBoost.MRF: Boosted Markov Random Forests and Application to Multilevel Activity Recognition.
Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), 2006


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