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Matteo Fasiolo
Matteo Fasiolo
Senior Lecturer in Statistical Science, University of Bristol
Verified email at bristol.ac.uk - Homepage
Title
Cited by
Cited by
Year
Fast calibrated additive quantile regression
M Fasiolo, SN Wood, M Zaffran, R Nedellec, Y Goude
Journal of the American Statistical Association 116 (535), 1402-1412, 2021
2442021
Scalable visualisation methods for modern Generalized Additive Models
M Fasiolo, R Nedellec, Y Goude, SN Wood
Journal of computational and Graphical Statistics, 2020
1882020
A comparison of inferential methods for highly non-linear state space models in ecology and epidemiology
M Fasiolo, N Pya, S Wood
Statistical Science 31 (1), 96-118, 2016
832016
Practice makes perfect: The consequences of lexical proficiency for articulation
F Tomaschek, BV Tucker, M Fasiolo, RH Baayen
Linguistics Vanguard 4 (s2), 20170018, 2018
802018
A generalized Fellner‐Schall method for smoothing parameter optimization with application to Tweedie location, scale and shape models
SN Wood, M Fasiolo
Biometrics 73 (4), 1071-1081, 2017
712017
qgam: Bayesian non-parametric quantile regression modelling in R
M Fasiolo, SN Wood, M Zaffran, R Nedellec, Y Goude
arXiv preprint arXiv:2007.03303, 2020
642020
Rfast: a collection of efficient and extremely fast R functions
M Papadakis, M Tsagris, M Dimitriadis, S Fafalios, I Tsamardinos, ...
R package version 2 (1), 2020
552020
Predicting pasture biomass using a statistical model and machine learning algorithm implemented with remotely sensed imagery
D De Rosa, B Basso, M Fasiolo, J Friedl, B Fulkerson, PR Grace, ...
Computers and Electronics in Agriculture 180, 105880, 2021
492021
Probabilistic forecasting of regional net-load with conditional extremes and gridded NWP
J Browell, M Fasiolo
IEEE Transactions on Smart Grid 12 (6), 5011-5019, 2021
422021
An extended empirical saddlepoint approximation for intractable likelihoods
M Fasiolo, SN Wood, F Hartig, MV Bravington
402018
Clinical predictors of pacemaker implantation in patients with syncope receiving implantable loop recorder with or without ECG conduction abnormalities
N Ahmed, A Frontera, A Carpenter, S Cataldo, GM Connolly, M Fasiolo, ...
Pacing and Clinical Electrophysiology 38 (8), 934-941, 2015
352015
Soil organic carbon stocks in European croplands and grasslands: How much have we lost in the past decade?
D De Rosa, C Ballabio, E Lugato, M Fasiolo, A Jones, P Panagos
Global Change Biology 30 (1), e16992, 2024
342024
Robust neural posterior estimation and statistical model criticism
D Ward, P Cannon, M Beaumont, M Fasiolo, S Schmon
Advances in Neural Information Processing Systems 35, 33845-33859, 2022
272022
Stochastic particle flow for nonlinear high-dimensional filtering problems
FE De Melo, S Maskell, M Fasiolo, F Daum
arXiv preprint arXiv:1511.01448, 2015
262015
COVID-19 and the difficulty of inferring epidemiological parameters from clinical data
SN Wood, EC Wit, M Fasiolo, PJ Green
The Lancet. Infectious Diseases 21 (1), 27, 2021
232021
An introduction to mvnfast
M Fasiolo
R package version 0.1 6, 2016
182016
Daily peak electrical load forecasting with a multi-resolution approach
Y Amara-Ouali, M Fasiolo, Y Goude, H Yan
International Journal of Forecasting 39 (3), 1272-1286, 2023
172023
An introduction to synlik (2014)
M Fasiolo, S Wood
R package version 0.1 1, 2014
152014
Rfast: A Collection of Efficient and Extremely Fast R Functions. 2021
M Papadakis, M Tsagris, M Dimitriadis, S Fafalios, I Tsamardinos, ...
URL https://CRAN. R-project. org/package= Rfast. R package version 2 (3), 656, 0
15
Drivers of interannual and intra‐annual variability of dissolved organic carbon concentration in the River Thames between 1884 and 2013
V Noacco, CJ Duffy, T Wagener, F Worrall, M Fasiolo, NJK Howden
Hydrological Processes 33 (6), 994-1012, 2019
142019
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