Matteo Fasiolo
Matteo Fasiolo
Lecturer in Statistical Science, University of Bristol
Verified email at - Homepage
Cited by
Cited by
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
Scalable visualisation methods for modern Generalized Additive Models
M Fasiolo, R Nedellec, Y Goude, SN Wood
Journal of computational and Graphical Statistics, 2020
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
Practice makes perfect: The consequences of lexical proficiency for articulation
F Tomaschek, BV Tucker, M Fasiolo, RH Baayen
Linguistics Vanguard 4 (s2), 20170018, 2018
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
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
An extended empirical saddlepoint approximation for intractable likelihoods
M Fasiolo, SN Wood, F Hartig, MV Bravington
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
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
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
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
Stochastic particle flow for nonlinear high-dimensional filtering problems
FE De Melo, S Maskell, M Fasiolo, F Daum
arXiv preprint arXiv:1511.01448, 2015
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), 27-28, 2021
An introduction to synlik (2014)
M Fasiolo, S Wood
R package version 0.1 1, 2014
mgcViz: Visualisations for generalized additive models
M Fasiolo, R Nedellec, Y Goude, C Capezza, SN Wood
Computer software]. https://CRAN. R-project. org/package= mgcViz, 2020
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
An introduction to mvnfast
M Fasiolo
R package version 0.1 6, 2016
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
Additive stacking for disaggregate electricity demand forecasting
C Capezza, B Palumbo, Y Goude, SN Wood, M Fasiolo
The Annals of Applied Statistics 15 (2), 727-746, 2021
Langevin incremental mixture importance sampling
M Fasiolo, FE de Melo, S Maskell
Statistics and Computing 28, 549-561, 2018
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