| 2022 | WWW | Universal Graph Transformer Self-Attention Networks. | Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung |
| 2022 | WWW | QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings. | Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dinh Q. Phung |
| 2021 | ACML | Quaternion Graph Neural Networks. | Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Q. Phung |
| 2020 | CIKM | A Capsule Network-based Model for Learning Node Embeddings. | Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung |
| 2019 | AAAI | Robust Anomaly Detection in Videos Using Multilevel Representations. | Hung Vu, Tu Dinh Nguyen, Trung Le, Wei Luo, Dinh Q. Phung |
| 2019 | IJCAI | Three-Player Wasserstein GAN via Amortised Duality. | Nhan Dam, Quan Hoang, Trung Le, Tu Dinh Nguyen, Hung Bui, Dinh Phung |
| 2019 | IJCAI | Learning Generative Adversarial Networks from Multiple Data Sources. | Trung Le, Quan Hoang, Hung Vu, Tu Dinh Nguyen, Hung Bui, Dinh Q. Phung |
| 2019 | NAACL | A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization. | Dai Quoc Nguyen, Thanh Vu, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung |
| 2018 | ACML | Clustering Induced Kernel Learning. | Khanh Nguyen, Nhan Dam, Trung Le, Tu Dinh Nguyen, Dinh Q. Phung |
| 2018 | ACML | Batch Normalized Deep Boltzmann Machines. | Hung Vu, Tu Dinh Nguyen, Trung Le, Wei Luo, Dinh Q. Phung |
| 2018 | ICLR | MGAN: Training Generative Adversarial Nets with Multiple Generators. | Quan Hoang, Tu Dinh Nguyen, Trung Le, Dinh Q. Phung |
| 2018 | ICPR | Bayesian Multi-Hyperplane Machine for Pattern Recognition. | Khanh Nguyen, Trung Le, Tu Dinh Nguyen, Dinh Q. Phung |
| 2018 | IJCAI | Geometric Enclosing Networks. | Trung Le, Hung Vu, Tu Dinh Nguyen, Dinh Q. Phung |
| 2018 | KDD | Robust Bayesian Kernel Machine via Stein Variational Gradient Descent for Big Data. | Khanh Nguyen, Trung Le, Tu Dinh Nguyen, Dinh Q. Phung, Geoffrey I. Webb |
| 2018 | NAACL | A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network. | Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Q. Phung |
| 2018 | PAKDD | Trans2Vec: Learning Transaction Embedding via Items and Frequent Itemsets. | Dang Nguyen, Tu Dinh Nguyen, Wei Luo, Svetha Venkatesh |
| 2018 | SDM | Learning Graph Representation via Frequent Subgraphs. | Dang Nguyen, Wei Luo, Tu Dinh Nguyen, Svetha Venkatesh, Dinh Q. Phung |
| 2017 | DSAA | Animal Recognition and Identification with Deep Convolutional Neural Networks for Automated Wildlife Monitoring. | Hung Nguyen, Sarah J. Maclagan, Tu Dinh Nguyen, Thin Nguyen, Paul Flemons, Kylie Andrews, Euan G. Ritchie, Dinh Q. Phung |
| 2017 | ICDM | GoGP: Fast Online Regression with Gaussian Processes. | Trung Le, Khanh Nguyen, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung |
| 2017 | IJCAI | Large-scale Online Kernel Learning with Random Feature Reparameterization. | Tu Dinh Nguyen, Trung Le, Hung Bui, Dinh Q. Phung |
| 2017 | PAKDD | Energy-Based Localized Anomaly Detection in Video Surveillance. | Hung Vu, Tu Dinh Nguyen, Anthony Travers, Svetha Venkatesh, Dinh Q. Phung |
| 2017 | UAI | Supervised Restricted Boltzmann Machines. | Tu Dinh Nguyen, Dinh Q. Phung, Viet Huynh, Trung Le |
| 2016 | ACML | Multiple Kernel Learning with Data Augmentation. | Khanh Nguyen, Trung Le, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung |
| 2016 | AISTATS | Nonparametric Budgeted Stochastic Gradient Descent. | Trung Le, Vu Nguyen, Tu Dinh Nguyen, Dinh Q. Phung |
| 2016 | ICDM | One-Pass Logistic Regression for Label-Drift and Large-Scale Classification on Distributed Systems. | Vu Nguyen, Tu Dinh Nguyen, Trung Le, Svetha Venkatesh, Dinh Q. Phung |
| 2016 | ICPR | Distributed data augmented support vector machine on Spark. | Tu Dinh Nguyen, Vu Nguyen, Trung Le, Dinh Q. Phung |
| 2016 | UAI | Budgeted Semi-supervised Support Vector Machine . | Trung Le, Phuong Duong, Mi Dinh, Tu Dinh Nguyen, Vu Nguyen, Dinh Q. Phung |
| 2015 | AAAI | Tensor-Variate Restricted Boltzmann Machines. | Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh |
| 2015 | PAKDD | Stabilizing Sparse Cox Model Using Statistic and Semantic Structures in Electronic Medical Records. | Shivapratap Gopakumar, Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh |
| 2013 | ACML | Learning Parts-based Representations with Nonnegative Restricted Boltzmann Machine. | Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh |
| 2013 | PAKDD | Latent Patient Profile Modelling and Applications with Mixed-Variate Restricted Boltzmann Machine. | Tu Dinh Nguyen, Truyen Tran, Dinh Q. Phung, Svetha Venkatesh |