Examining microbe-metabolite correlations by linear methods T. P. Quinn, I. Erb 2021 / Vol. 18, pp. 37 - 39 / Nature Methods
Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization K. Do, T. Tran, S. Venkatesh 2021 / The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI)
Examining microbe–metabolite correlations by linear methods T. P. Quinn, I. Erb 2021 / Vol. 18, pp. 37 - 39 / Nature Methods
Genomic mutations and changes in protein secondary structure and solvent accessibility of SARS-CoV-2 (COVID-19) virus T. T. Nguyen, P. N. Pathirana, T. Nguyen, H. Nguyen, A. Bhatti, D. C. Nguyen, D. T. Nguyen, N. D. Nguyen, D. Creighton, M. Abdelrazek 2021 / Scientific Reports
Distributional Reinforcement Learning via Moment Matching T. T. Nguyen, S. Gupta, S. Venkatesh 2021 / pp. accepted on 02/10/2020 / The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI)
Test set verification is an essential step in model building T. P. Quinn, V. Le, A. P. A. Cardilini 2021 / Vol. 12, pp. 127 - 129 / Methods in Ecology and Evolution
Sparse Spectrum Gaussian Process for Bayesian Optimization A. Yang, C. Li, S. Rana, S. Gupta, S. Venkatesh 2021 / pp. To appear / Proceedings of the 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2021)
High Dimensional Level Set Estimation with Bayesian Neural Network H. Ha, S. Gupta, S. Rana, S. Venkatesh 2021 / pp. To appear / Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence
Coupling machine learning with 3D bioprinting to fast track optimisation of extrusion printing K. Ruberu, M. Senadeera, S. Rana, S. Gupta, J. Chung, Z. Yue, S. Venkatesh, G. Wallace 2021 / Vol. 22, pp. 100914 / Applied Materials Today
Goal-driven Long-Term Trajectory Prediction H. Tran, V. Le, T. Tran 2021 / pp. 796 - 805 / Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision
Graph convolutional networks for drug response prediction T. Nguyen, G. Nguyen, T. Nguyen, D. Le 2021 / IEEE/ACM Transactions on Computational Biology and Bioinformatics
Editorial: Compositional data analysis and related methods applied to genomics—a first special issue from NAR Genomics and Bioinformatics I. Erb, G. B. Gloor, T. P. Quinn 2020 / Vol. 2 / NAR Genomics and Bioinformatics
Amalgams: data-driven amalgamation for the dimensionality reduction of compositional data T. P. Quinn, I. Erb 2020 / Vol. 2 / NAR Genomics and Bioinformatics
Self-Attentive Associative Memory H. Le, T. Tran, S. Venkatesh 2020 / pp. 5682 - 5691 / Proceedings of the 37th International Conference on Machine Learning (ICML)
Enriching Programming Student Feedback with Audio Comments J. Renzella, A. Cain 2020 / pp. 173 - 183 / 2020 IEEE/ACM 42nd International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET)
User-centred tooling for modelling of big data applications H. Khalajzadeh, T. Verma, A. Simmons, J. Grundy, M. Abdelrazek, J. Hosking 2020 / pp. 1 - 5 / Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings
Using Spatiotemporal Distribution of Geocoded Twitter Data to Predict US County-Level Health Indices T. Nguyen, M. Larsen, B. O'Dea, H. Nguyen, D. T. Nguyen, J. Yearwood, D. Phung, S. Venkatesh, H. Christensen 2020 / Vol. 110, pp. 620 - 628 / Future Generation Computer Systems
Learning Transferable Domain Priors for Safe Exploration in Reinforcement Learning T. G. Karimpanal, S. Rana, S. Gupta, T. Tran, S. Venkatesh 2020 / Proceedings of the International Joint Conference on Neural Networks (IJCNN)
A Revised Open Source Usability Defect Classification Taxonomy N. S. M. Yusop, J. Grundy, J. Schneider, R. Vasa 2020 / pp. 106396 / Information and Software Technology
Learning to Abstract and Predict Human Actions R. Morais, V. Le, T. Tran, S. Venkatesh 2020 / Proceedings of the The British Machine Vision Conference (BMVC)
