Likelihood-free parameter estimation with neural Bayes estimators M Sainsbury-Dale, A Zammit-Mangion, R Huser The American Statistician 78 (1), 1-14, 2024 | 41* | 2024 |
Basis-function models in spatial statistics N Cressie, M Sainsbury-Dale, A Zammit-Mangion Annual Review of Statistics and Its Application 9, 373-400, 2022 | 41 | 2022 |
Neural Bayes estimators for censored inference with peaks-over-threshold models J Richards, M Sainsbury-Dale, A Zammit-Mangion, R Huser Journal of Machine Learning Research 25 (390), 1-49, 2024 | 22* | 2024 |
Neural Bayes estimators for irregular spatial data using graph neural networks M Sainsbury-Dale, J Richards, A Zammit-Mangion, R Huser arXiv preprint arXiv:2310.02600, 2023 | 19 | 2023 |
Neural Methods for Amortized Inference A Zammit-Mangion, M Sainsbury-Dale, R Huser arXiv preprint arXiv:2404.12484, 2024 | 13 | 2024 |
Modeling Big, Heterogeneous, Non-Gaussian Spatial and Spatio-Temporal Data Using FRK M Sainsbury-Dale, A Zammit-Mangion, N Cressie Journal of Statistical Software 108, 1-39, 2024 | 12 | 2024 |
FRK: Fixed Rank Kriging A Zammit-Mangion, M Sainsbury-Dale R package version 2.1.5, 2021 | 9 | 2021 |
Neural Parameter Estimation with Incomplete Data M Sainsbury-Dale, A Zammit-Mangion, N Cressie, R Huser arXiv preprint arXiv:2501.04330, 2025 | | 2025 |
Efficient Inference for Spatial and Spatio-Temporal Statistical Models Using Basis-Function and Deep-Learning Methods M Sainsbury-Dale Bulletin of the Australian Mathematical Society, 1-2, 2024 | | 2024 |