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Tullia Padellini
Tullia Padellini
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Title
Cited by
Cited by
Year
Long-term exposure to air-pollution and COVID-19 mortality in England: a hierarchical spatial analysis
G Konstantinoudis, T Padellini, J Bennett, B Davies, M Ezzati, ...
Environment international 146, 106316, 2021
1692021
Improving local prevalence estimates of SARS-CoV-2 infections using a causal debiasing framework
G Nicholson, B Lehmann, T Padellini, KB Pouwels, R Jersakova, J Lomax, ...
Nature microbiology 7 (1), 97-107, 2022
38*2022
Time varying association between deprivation, ethnicity and SARS-CoV-2 infections in England: A population-based ecological study
T Padellini, R Jersakova, PJ Diggle, C Holmes, RE King, BCL Lehmann, ...
The Lancet Regional Health–Europe 15, 2022
212022
Interoperability of statistical models in pandemic preparedness: Principles and reality
G Nicholson, M Blangiardo, M Briers, PJ Diggle, TE Fjelde, H Ge, ...
Statistical Science 37 (2), 183-206, 2022
182022
Model-aware quantile regression for discrete data
T Padellini, H Rue
arXiv preprint arXiv:1804.03714, 2018
13*2018
A mathematical programming approach to sparse canonical correlation analysis
L Amorosi, T Padellini, J Puerto, C Valverde
Expert Systems with Applications, 121293, 2023
52023
A Bayesian hierarchical small area population model accounting for data source specific methodologies from American Community Survey, Population Estimates Program, and …
EN Peterson, RC Nethery, T Padellini, JT Chen, BA Coull, FB Piel, ...
The Annals of Applied Statistics 18 (2), 1565-1595, 2024
42024
Persistence Flamelets: Topological Invariants for Scale Spaces
T Padellini, P Brutti
Journal of Computational and Graphical Statistics, 1-27, 2022
4*2022
Supervised learning with indefinite topological Kernels
T Padellini, P Brutti
Statistics 55 (4), 765-786, 2021
32021
Response to “Re: Long-term exposure to air-pollution and COVID-19 mortality in England: A hierarchical spatial analysis”
G Konstantinoudis, T Padellini, J Bennett, B Davies, M Ezzati, ...
Environment International 150, 106427, 2021
12021
Hierarchical Graphical Model for Learning Functional Network Determinants
E Aliverti, L Forastiere, T Padellini, S Paganin, E Wit
Studies in Neural Data Science: StartUp Research 2017, Siena, Italy, June 25 …, 2018
2018
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