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2024

Journal Article

Functional mixtures-of-experts

Chamroukhi, Faïcel, Pham, Nhat Thien, Hoang, Van Hà and McLachlan, Geoffrey J. (2024). Functional mixtures-of-experts. Statistics and Computing, 34 (3) 98. doi: 10.1007/s11222-023-10379-0

Functional mixtures-of-experts

2024

Journal Article

Semi‐supervised Gaussian mixture modelling with a missing‐data mechanism in R

Lyu, Ziyang, Ahfock, Daniel, Thompson, Ryan and McLachlan, Geoffrey J. (2024). Semi‐supervised Gaussian mixture modelling with a missing‐data mechanism in R. Australian and New Zealand Journal of Statistics, 66 (2), 146-162. doi: 10.1111/anzs.12413

Semi‐supervised Gaussian mixture modelling with a missing‐data mechanism in R

2024

Journal Article

An overview of skew distributions in model-based clustering

Lee, Sharon X. and McLachlan, Geoffrey J. (2024). An overview of skew distributions in model-based clustering. Science Talks, 9 100298, 100298. doi: 10.1016/j.sctalk.2024.100298

An overview of skew distributions in model-based clustering

2024

Journal Article

A mineralogy characterisation technique for copper ore in flotation pulp using deep learning machine vision with optical microscopy

Koh, Edwin J.Y., Amini, Eiman, Spier, Carlos A., McLachlan, Geoffrey J., Xie, Weiguo and Beaton, Nick (2024). A mineralogy characterisation technique for copper ore in flotation pulp using deep learning machine vision with optical microscopy. Minerals Engineering, 205 108481, 1-16. doi: 10.1016/j.mineng.2023.108481

A mineralogy characterisation technique for copper ore in flotation pulp using deep learning machine vision with optical microscopy

2023

Journal Article

Robust clustering based on finite mixture of multivariate fragmental distributions

Maleki, Mohsen, McLachlan, Geoffrey J. and Lee, Sharon X. (2023). Robust clustering based on finite mixture of multivariate fragmental distributions. Statistical Modelling, 23 (3), 247-272. doi: 10.1177/1471082X211048660

Robust clustering based on finite mixture of multivariate fragmental distributions

2023

Journal Article

Semi-supervised learning of classifiers from a statistical perspective: a brief review

Ahfock, Daniel and McLachlan, Geoffrey J. (2023). Semi-supervised learning of classifiers from a statistical perspective: a brief review. Econometrics and Statistics, 26, 124-138. doi: 10.1016/j.ecosta.2022.03.007

Semi-supervised learning of classifiers from a statistical perspective: a brief review

2023

Journal Article

Order selection with confidence for finite mixture models

Nguyen, Hien D., Fryer, Daniel and McLachlan, Geoffrey J. (2023). Order selection with confidence for finite mixture models. Journal of the Korean Statistical Society, 52 (1), 154-184. doi: 10.1007/s42952-022-00195-z

Order selection with confidence for finite mixture models

2023

Journal Article

Approximation of probability density functions via location-scale finite mixtures in Lebesgue spaces

Nguyen, TrungTin, Chamroukhi, Faicel, Nguyen, Hien D. and McLachlan, Geoffrey J. (2023). Approximation of probability density functions via location-scale finite mixtures in Lebesgue spaces. Communications in Statistics - Theory and Methods, 52 (14), 1-12. doi: 10.1080/03610926.2021.2002360

Approximation of probability density functions via location-scale finite mixtures in Lebesgue spaces

2023

Journal Article

A new algorithm for support vector regression with automatic selection of hyperparameters

Wang, You-Gan, Wu, Jinran, Hu, Zhi-Hua and McLachlan, Geoffrey J. (2023). A new algorithm for support vector regression with automatic selection of hyperparameters. Pattern Recognition, 133 108989, 1-9. doi: 10.1016/j.patcog.2022.108989

A new algorithm for support vector regression with automatic selection of hyperparameters

2023

Journal Article

Joint frailty modeling of time-to-event data to elicit the evolution pathway of events: a generalized linear mixed model approach

Ng, Shu Kay, Tawiah, Richard, McLachlan, Geoffrey J. and Gopalan, Vinod (2023). Joint frailty modeling of time-to-event data to elicit the evolution pathway of events: a generalized linear mixed model approach. Biostatistics, 24 (1), 108-123. doi: 10.1093/biostatistics/kxab037

Joint frailty modeling of time-to-event data to elicit the evolution pathway of events: a generalized linear mixed model approach

2023

Conference Publication

Using cellular composition estimated from bulk RNA-seq data to suggest cellular level markers for melanoma survival

Zhang, Min, Basford, Kaye, Arief, Vivi, McLachlan, Geoff and Nguyen, Quan (2023). Using cellular composition estimated from bulk RNA-seq data to suggest cellular level markers for melanoma survival. IBS-AR/SEEM Conference, Bay of Islands, Aotearoa, New Zealand, 27 November - 1 December 2023.

Using cellular composition estimated from bulk RNA-seq data to suggest cellular level markers for melanoma survival

2022

Conference Publication

Exploratory data analysis of TCGA skin cutaneous melanoma RNA-seq data

Zhang, Min, Arief, Vivi, McLachlan, Geoffrey, Nguyen, Quan and Basford, Kaye (2022). Exploratory data analysis of TCGA skin cutaneous melanoma RNA-seq data. Australasian Applied Statistics Conference (AASC), Inverloch, VIC Australia, 28 November - 2 December 2022.

Exploratory data analysis of TCGA skin cutaneous melanoma RNA-seq data

2022

Journal Article

An Automated Machine learning (AutoML) approach to regression models in minerals processing with case studies of developing industrial comminution and flotation models

Koh, Edwin J. Y., Amini, Eiman, Gaur, Shruti, Becerra Maquieira, Miguel, Jara Heck, Christian, McLachlan, Geoffrey J. and Beaton, Nick (2022). An Automated Machine learning (AutoML) approach to regression models in minerals processing with case studies of developing industrial comminution and flotation models. Minerals Engineering, 189 107886, 107886. doi: 10.1016/j.mineng.2022.107886

An Automated Machine learning (AutoML) approach to regression models in minerals processing with case studies of developing industrial comminution and flotation models

2022

Journal Article

A spatial heterogeneity mixed model with skew-elliptical distributions

Farzammehr, Mohadeseh Alsadat and McLachlan, Geoffrey J. (2022). A spatial heterogeneity mixed model with skew-elliptical distributions. Communications for Statistical Applications and Methods, 29 (3), 373-391. doi: 10.29220/csam.2022.29.3.373

A spatial heterogeneity mixed model with skew-elliptical distributions

2022

Other Outputs

Detecting accounting fraud with noisy labels

Ahfock, Daniel, McLachlan, Geoffrey, Yang, Liu and Zhu, Min (2022). Detecting accounting fraud with noisy labels. UQ Business School.

Detecting accounting fraud with noisy labels

2022

Journal Article

Statistical file-matching of non-Gaussian data: a game theoretic approach

Ahfock, Daniel, Pyne, Saumyadipta and McLachlan, Geoffrey J. (2022). Statistical file-matching of non-Gaussian data: a game theoretic approach. Computational Statistics and Data Analysis, 168 107387, 1-16. doi: 10.1016/j.csda.2021.107387

Statistical file-matching of non-Gaussian data: a game theoretic approach

2022

Journal Article

An overview of skew distributions in model-based clustering

Lee, Sharon X. and McLachlan, Geoffrey J. (2022). An overview of skew distributions in model-based clustering. Journal of Multivariate Analysis, 188 104853, 1-14. doi: 10.1016/j.jmva.2021.104853

An overview of skew distributions in model-based clustering

2021

Journal Article

Approximations of conditional probability density functions in Lebesgue spaces via mixture of experts models

Nguyen, Hien Duy, Nguyen, TrungTin, Chamroukhi, Faicel and McLachlan, Geoffrey John (2021). Approximations of conditional probability density functions in Lebesgue spaces via mixture of experts models. Journal of Statistical Distributions and Applications, 8 (1) 13. doi: 10.1186/s40488-021-00125-0

Approximations of conditional probability density functions in Lebesgue spaces via mixture of experts models

2021

Journal Article

Utilising convolutional neural networks to perform fast automated modal mineralogy analysis for thin-section optical microscopy

Koh, Edwin J. Y., Amini, Eiman, McLachlan, Geoffrey J. and Beaton, Nick (2021). Utilising convolutional neural networks to perform fast automated modal mineralogy analysis for thin-section optical microscopy. Minerals Engineering, 173 107230, 107230. doi: 10.1016/j.mineng.2021.107230

Utilising convolutional neural networks to perform fast automated modal mineralogy analysis for thin-section optical microscopy

2021

Conference Publication

AEGC Machine Learning Workshop presentation

Chatterjee, Robindra, Valenta, Richard, McLachlan, Geoffrey and Weatherley, Dion (2021). AEGC Machine Learning Workshop presentation. Australian Exploration Geoscience Conference, Online, 14-17 September 2021.

AEGC Machine Learning Workshop presentation