| 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 | 202 | 2021 |
| Scalable visualisation methods for modern Generalized Additive Models M Fasiolo, R Nedellec, Y Goude, SN Wood Journal of computational and Graphical Statistics, 2020 | 150 | 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 | 78 | 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 | 71 | 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 | 60 | 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 | 40 | 2020 |
| An extended empirical saddlepoint approximation for intractable likelihoods M Fasiolo, SN Wood, F Hartig, MV Bravington | 35 | 2018 |
| 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 | 34 | 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 | 32 | 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 | 28 | 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 | 23 | 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 | 22 | 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 | 19 | 2021 |
| An introduction to synlik (2014) M Fasiolo, S Wood R package version 0.1 1, 2014 | 15 | 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 | 12 | 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 | 12 | 2019 |
| An introduction to mvnfast M Fasiolo R package version 0.1 6, 2016 | 12 | 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 | 11 | 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 | 11 | 2021 |
| Langevin incremental mixture importance sampling M Fasiolo, FE de Melo, S Maskell Statistics and Computing 28, 549-561, 2018 | 11 | 2018 |
