| Fresh vs. frozen human decomposition–A preliminary investigation of lipid degradation products as biomarkers of post-mortem interval M Ueland, S Collins, L Maestrini, SL Forbes, S Luong Forensic Chemistry 24, 100335, 2021 | 17 | 2021 |
| Fitting structural equation models via variational approximations KD Dang, L Maestrini Structural Equation Modeling: A Multidisciplinary Journal 29 (6), 839-853, 2022 | 10 | 2022 |
| The Inverse G-Wishart distribution and variational message passing L Maestrini, MP Wand Australian and New Zealand Journal of Statistics 63 (3), 517-541, 2021 | 8 | 2021 |
| A variational inference framework for inverse problems L Maestrini, RG Aykroyd, MP Wand Computational Statistics & Data Analysis 202, 108055, 2025 | 7 | 2025 |
| A preliminary investigation to determine the suitability of pigs as human analogues for post-mortem lipid analysis S Collins, L Maestrini, M Ueland, B Stuart Talanta Open 5, 100100, 2022 | 6 | 2022 |
| Variational message passing for skew t regression L Maestrini, MP Wand Stat 7 (1), e196, 2018 | 6 | 2018 |
| Restricted maximum likelihood estimation in generalized linear mixed models L Maestrini, FKC Hui, AH Welsh arXiv preprint arXiv:2402.12719, 2024 | 4 | 2024 |
| Sparse linear mixed model selection via streamlined variational Bayes E Degani, L Maestrini, D Toczydlowska, MP Wand Electronic Journal of Statistics 16 (2), 5182-5225, 2022 | 4 | 2022 |
| Second term improvement to generalized linear mixed model asymptotics L Maestrini, A Bhaskaran, MP Wand Biometrika 111 (3), 1077-1084, 2024 | 2 | 2024 |
| Simultaneous coefficient clustering and sparsity for multivariate mixed models FKC Hui, KD Dang, L Maestrini Journal of Computational and Graphical Statistics, 1-12, 2024 | 1 | 2024 |
| On variational approximations for frequentist and Bayesian inference L Maestrini Università degli Studi di Padova, 2018 | 1 | 2018 |
| Variational approximations for frequentist and Bayesian inference L Maestrini, MP Wand 49th Scientific Meeting of the Italian Statistical Society, 1447-1452, 2018 | 1 | 2018 |
| Variational Bayes for Mixture of Gaussian Structural Equation Models KD Dang, L Maestrini, FKC Hui arXiv preprint arXiv:2407.08140, 2024 | | 2024 |
| Homogeneity pursuit and variable selection in regression models for multivariate abundance data FKC Hui, L Maestrini, AH Welsh Biometrics 80 (1), ujad001, 2024 | | 2024 |
| Stochastic variational inference for GARCH models H Xuan, L Maestrini, F Chen, C Grazian Statistics and Computing 34 (1), 45, 2024 | | 2024 |
| The use of generalized linear mixed models to investigate postmortem lipids in textiles S Collins, L Maestrini, FKC Hui, B Stuart, M Ueland Iscience 26 (8), 2023 | | 2023 |
| Model fitting and Bayesian inference via power expectation propagation E Degani, L Maestrini, M Bernardi 50th Scientific Meeting of the Italian Statistical Society, 1026-1031, 2021 | | 2021 |
| Variational message passing for Skew t regression L Maestrini, MP Wand 33rd International Workshop on Statistical Modelling, 204-208, 2018 | | 2018 |
| Pairs trading: a new approach based on the Beveridge-Nelson decomposition L Maestrini Politecnico di Milano, 2015 | | 2015 |
| Variational Deep Learning M Lin, G Livieri, L Maestrini, M Bernardi | | |
Matt WandDistinguished Professor of Statistics, University of Technology SydneyVerified email at uts.edu.au
