| Machine learning can guide food security efforts when primary data are not available G Martini, A Bracci, L Riches, S Jaiswal, M Corea, J Rivers, A Husain, ... Nature Food 3 (9), 716-728, 2022 | 62 | 2022 |
| On the forecastability of food insecurity P Foini, M Tizzoni, G Martini, D Paolotti, E Omodei Scientific Reports 13 (1), 2793, 2023 | 22 | 2023 |
| A predictive pedestrian crash model based on artificial intelligence techniques M Meocci, V Branzi, G Martini, R Arrighi, I Petrizzo Applied Sciences 11 (23), 11364, 2021 | 9 | 2021 |
| Structural and load parameter estimation of a real‐world reinforced concrete slab bridge using measurements and Bayesian statistics Á Rózsás, A Slobbe, G Martini, R Jansen Structural Concrete 23 (6), 3569-3600, 2022 | 4 | 2022 |
| Impact of food-related conflicts on self-reported food insecurity S Fiandrino, C Dowd, G Martini, Y Mejova, E Omodei, D Paolotti, ... Frontiers in Sustainable Food Systems 7, 1239992, 2023 | 2 | 2023 |
| Early warning of complex climate risk with integrated artificial intelligence M Reichstein, V Benson, G Camps-Valls, H Boran, C Fearnley, ... | 1 | 2024 |
| Causal machine learning for sustainable agroecosystems V Sitokonstantinou, EDS Porras, JC Bautista, M Piles, I Athanasiadis, ... arXiv preprint arXiv:2408.13155, 2024 | | 2024 |
| Forecasting Food Security with Reservoir Computing J Herteux, C Räth, A Baha, G Martini, D Piovani Verhandlungen der DPG, 2024 | | 2024 |
| Forecasting Trends in Food Security: a Reservoir Computing Approach J Herteux, C Räth, A Baha, G Martini, D Piovani Arxiv, 2023 | | 2023 |
