| Does cytolysis by CD8+ T cells drive immune escape in HIV infection? M Balamurali, J Petravic, L Loh, S Alcantara, SJ Kent, MP Davenport The Journal of Immunology 185 (9), 5093-5101, 2010 | 47 | 2010 |
| t-SNE based visualisation and clustering of geological domain M Balamurali, A Melkumyan Neural Information Processing: 23rd International Conference, ICONIP 2016 …, 2016 | 28 | 2016 |
| An “escape clock” for estimating the turnover of SIV DNA in resting CD4+ T cells J Reece, J Petravic, M Balamurali, L Loh, S Gooneratne, R De Rose, ... PLoS pathogens 8 (4), e1002615, 2012 | 26 | 2012 |
| A comparison of t-SNE, SOM and SPADE for identifying material type domains in geological data M Balamurali, K Silversides, A Melkumyan Computers & Geosciences, 2019 | 17 | 2019 |
| Deep Learning-Based Artificial Intelligence to Investigate Targeted Nanoparticles’ Uptake in TNBC Cells R Ali, M Balamurali, P Varamini International Journal of Molecular Sciences 16070, 2022 | 16 | 2022 |
| Sample truncation strategies for outlier removal in geochemical data: the MCD robust distance approach versus t-SNE ensemble clustering R Leung, M Balamurali, A Melkumyan Mathematical Geosciences 53, 105-130, 2021 | 14 | 2021 |
| t-Distributed Stochastic Neighbor Embedding M Balamurali Encyclopedia of Mathematical Geosciences, 1-9, 2021 | 12 | 2021 |
| Complexity of the inoculum determines the rate of reversion of SIV Gag CD8 T cell mutant virus and outcome of infection L Loh, JC Reece, CS Fernandez, S Alcantara, R Center, J Howard, ... PLoS Pathogens 5 (4), e1000378, 2009 | 12 | 2009 |
| A Bayesian method for estimating uncertainty in excavated material M Balamurali International Journal of Mining, Reclamation and Environment, 2021 | 6 | 2021 |
| Surface Warping Incorporating Machine Learning Assisted Domain Likelihood Estimation: A New Paradigm in Mine Geology Modelling and Automation R Leung, M Balamurali, A Lowe Mathematical Geosciences, 2021 | 6 | 2021 |
| Machine learning classification of geochemical and geophysical data L Huang, M Balamurali, KL Silversides Mining goes Digital, 101-105, 2019 | 6 | 2019 |
| Deep learning-based motion estimation for uninterrupted tracking of awake rodents in PET S Zhang, M Balamurali, A Kyme 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference …, 2018 | 5 | 2018 |
| Automated identification of geological domains for exploration assays with ambiguous initial domain assignment in an iron ore deposit M Balamurali, A Melkumyan Ninth International Mining Geology Conference, pp 99–106, 2014 | 5 | 2014 |
| Detection of Outliers in Geochemical Data Using Ensembles of Subsets of Variables M Balamurali, A Melkumyan Mathematical Geosciences, 1-12, 2018 | 4 | 2018 |
| Multivariate outlier detection in geochemical data M Balamurali, A Melkumyan International Association of Mathematical Geosciences (IAMG 2015), pp. 602-610, 2015 | 4 | 2015 |
| Geological domain classification using multiple chemical elements and spatial information M Balamurali, A Melkumyan Application of Computers and Operations Research in the Mineral Industry …, 2015 | 4 | 2015 |
| Automatic excavator action recognition and localisation for untrimmed video using hybrid LSTM-Transformer networks A Martin, AJ Hill, KM Seiler, M Balamurali International Journal of Mining, Reclamation and Environment 38 (5), 353-372, 2024 | 2 | 2024 |
| SimMining-3D: Altitude-Aware 3D Object Detection in Complex Mining Environments: A Novel Dataset and ROS-Based Automatic Annotation Pipeline M Balamurali, E Mihankhah Australasian Joint Conference on Artificial Intelligence, 55-66, 2023 | 2 | 2023 |
| Load-Haul Cycle Segmentation with Hidden Semi-Markov Models G Markham, KM Seiler, M Balamurali, AJ Hill 2022 IEEE 18th International Conference on Automation Science and …, 2022 | 2 | 2022 |
| Improving geometry dynamic prediction of in-pit stockpiles using geospatial data and polygon models M Balamurali, KM Seiler The next digital transformation in mining, Application of Computers and …, 2021 | 2 | 2021 |
Arman MelkumyanSenior Research Fellow and Orebody Knowledge Theme Leader, Rio Tinto Centre for Mine在 acfr.usyd.edu.au 的电子邮件经过验证
