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Michael Bertolacci
Michael Bertolacci
Research Fellow, University of Wollongong
Verified email at uow.edu.au - Homepage
Title
Cited by
Cited by
Year
Are approximation algorithms for consensus clustering worthwhile?
M Bertolacci, A Wirth
Proceedings of the 2007 SIAM International Conference on Data Mining, 437-442, 2007
352007
Climate inference on daily rainfall across the Australian continent, 1876–2015
M Bertolacci, E Cripps, O Rosen, JW Lau, S Cripps
The Annals of Applied Statistics 13 (2), 683-712, 2019
62019
New algorithms research for first year students
A Wirth, M Bertolacci
Proceedings of the 11th annual SIGCSE conference on Innovation and …, 2006
62006
WOMBAT: A fully Bayesian global flux-inversion framework
A Zammit-Mangion, M Bertolacci, J Fisher, A Stavert, ML Rigby, Y Cao, ...
arXiv preprint arXiv:2102.04004, 2021
42021
AdaptSPEC-X: Covariate-Dependent Spectral Modeling of Multiple Nonstationary Time Series
M Bertolacci, O Rosen, E Cripps, S Cripps
Journal of Computational and Graphical Statistics 31 (2), 436-454, 2022
32022
National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the Global Stocktake
B Byrne, DF Baker, S Basu, M Bertolacci, KW Bowman, D Carroll, ...
Earth System Science Data Discussions, 1-59, 2022
22022
From Many to One: Consensus Inference in a MIP
N Cressie, M Bertolacci, A Zammit‐Mangion
Geophysical Research Letters 49 (14), e2022GL098277, 2022
12022
A comparison of methods for modeling marginal non-zero daily rainfall across the Australian continent
M Bertolacci, E Cripps, O Rosen, S Cripps
arXiv preprint arXiv:1804.08807, 2018
12018
Inferring changes to the global carbon cycle with WOMBAT v2. 0, a hierarchical flux-inversion framework
M Bertolacci, A Zammit-Mangion, A Schuh, B Bukosa, J Fisher, Y Cao, ...
arXiv preprint arXiv:2210.10479, 2022
2022
Modelling the growth of atmospheric nitrous oxide using a global hierarchical inversion
AC Stell, M Bertolacci, A Zammit-Mangion, M Rigby, PJ Fraser, CM Harth, ...
Atmospheric Chemistry and Physics 22 (19), 12945-12960, 2022
2022
AdaptSPEC-X: Covariate-Dependent Spectral Modeling of Multiple Nonstationary Time Series
O Rosen, M Bertolacci, S Cripps, E Cripps
2022 Fall Central Sectional Meeting, 2022
2022
WOMBAT v1. 0: a fully Bayesian global flux-inversion framework
A Zammit-Mangion, M Bertolacci, J Fisher, A Stavert, M Rigby, Y Cao, ...
Geoscientific Model Development 15 (1), 45-73, 2022
2022
Corrigendum to “WOMBAT v1. 0: a fully Bayesian global flux-inversion framework” published in Geosci. Model Dev., 15, 45–73, 2022
A Zammit-Mangion, M Bertolacci, J Fisher, A Stavert, M Rigby, Y Cao, ...
2022
Top-down estimate of carbon stock changes in support of the Global Stocktake
B Byrne, D Baker, S Basu, M Bertolacci, KW Bowman, A Chatterjee, ...
AGU Fall Meeting Abstracts 2021, A51F-01, 2021
2021
AdaptSPEC-X: a spectral method for handling spatially-dependent nonstationarity
M Bertolacci
2021
WOMBAT: A fully Bayesian global flux-inversion framework
AZ Mangion, M Bertolacci, JA Fisher, A Stavert, Y Cao, ML Rigby, ...
AGU Fall Meeting 2020, 2020
2020
Hierarchical Bayesian mixture models for spatiotemporal data with nonstandard features
M Bertolacci, E Cripps, J Lau
2019
THE ANNALS
M BERTOLACCI, E CRIPPS, ORI ROSEN, JW LAU, S CRIPPS, ...
Supplement to “AdaptSPEC-X: Covariate Dependent Spectral Modeling of Multiple Nonstationary Time Series”
M Bertolacci, O Rosen, E Cripps, S Cripps
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Articles 1–19