Publications
Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization
Kien Do, Truyen Tran, Svetha Venkatesh
(2021), Vol. 35, pp. 7236-7244, AAAI 2021 : Proceedings of the 35th AAAI Conference on Artificial Intelligence, Virtual Event, E1
DeepProcess: Supporting Business Process Execution Using a MANN-Based Recommender System
A Khan, H Le, K Do, T Tran, A Ghose, H Dam, R Sindhgatta
(2021), Vol. 13121, pp. 19-33, ICSOC 2021 : Proceedings of the 19th Service-Oriented Computing Iternational Computing, Virtual Event, E1
Unsupervised Anomaly Detection on Temporal Multiway Data
D Nguyen, P Nguyen, K Do, S Rana, S Gupta, T Tran
(2020), pp. 1059-1066, SSCI 2020 : Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, Canberra, Australian Capital Territory, E1
Attentional multilabel learning over graphs: a message passing approach
K Do, T Tran, T Nguyen, S Venkatesh
(2019), Vol. 108, pp. 1757-1781, Machine Learning, C1
Graph transformation policy network for chemical reaction prediction
K Do, T Tran, S Venkatesh
(2019), pp. 750-760, KDD 2019 : Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, Anchorage, Alaska, E1
Energy-based anomaly detection for mixed data
K Do, T Tran, S Venkatesh
(2018), Vol. 57, pp. 413-435, Knowledge and Information Systems, C1
Knowledge graph embedding with multiple relation projections
K Do, T Tran, S Venkatesh
(2018), pp. 332-337, ICPR 2018: Proceedings of the 24th International Conference on Pattern Recognition, Beijing, China, E1
Outlier detection on mixed-type data: An energy-based approach
K Do, T Tran, D Phung, S Venkatesh
(2016), Vol. 10086 LNAI, pp. 111-125, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), E1
Funded Projects at Deakin
No Funded Projects at Deakin found
Supervisions
No completed student supervisions to report