Langevin incremental mixture importance sampling. - Matteo Fasiolo; Flávio Eler de Melo; Simon Maskell (Stat. Comput., 2018)

Predicting pasture biomass using a statistical model and machine learning algorithm implemented with remotely sensed imagery. - Daniele De Rosa; Bruno Basso; Matteo Fasiolo; Johannes Friedl; Bill Fulkerson; Peter R. Grace; David W. Rowlings (Comput. Electron. Agric., 2021)

Daily peak electrical load forecasting with a multi-resolution approach. - Yvenn Amara-Ouali; Matteo Fasiolo; Yannig Goude; Hui Yan (CoRR, 2021)

qgam: Bayesian Nonparametric Quantile Regression Modeling in R. - Matteo Fasiolo; Simon N. Wood; Margaux Zaffran; Raphaël Nedellec; Yannig Goude (J. Stat. Softw., 2021)

Probabilistic Forecasting of Regional Net-Load With Conditional Extremes and Gridded NWP. - Jethro Browell; Matteo Fasiolo (IEEE Trans. Smart Grid, 2021)

Robust Neural Posterior Estimation and Statistical Model Criticism. - Daniel Ward; Patrick Cannon; Mark Beaumont; Matteo Fasiolo; Sebastian M. Schmon (NeurIPS, 2022)

SoftCVI: Contrastive variational inference with self-generated soft labels. - Daniel Ward; Mark Beaumont; Matteo Fasiolo (ICLR, 2025)