Profile image of Kien Do

Dr Kien Do

STAFF PROFILE

Position

Research Fellow

Faculty

Applied Artificial Intel Inst

Department

A2I2P

Campus

Geelong Waurn Ponds Campus

Research interests

Adversarial Learning, Generative Models, Self-supervised Learning, Representation Learning, Causal Inference

Publications

Filter by

2021

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

conference

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

conference
2020

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

conference
2019

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, New York, N.Y., C1

journal article

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

conference
2018

Energy-based anomaly detection for mixed data

K Do, T Tran, S Venkatesh

(2018), Vol. 57, pp. 413-435, Knowledge and Information Systems, C1

journal article

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

conference
2016

Outlier detection on mixed-type data: an energy-based approach

D Do, D DO, T Tran, D Phung, S Venkatesh

(2016), Vol. 10086, pp. 111-125, ADMA 2016 : Proceedings of the 12th International Conference of Advanced Data Mining and Applications, Gold Coat, Queensland, E1

conference

Funded Projects at Deakin

No Funded Projects at Deakin found

Supervisions

No completed student supervisions to report