| Causal tree with instrumental variable: an extension of the causal tree framework to irregular assignment mechanisms FJ Bargagli Stoffi, G Gnecco International Journal of Data Science and Analytics 9 (3), 315-337, 2020 | 24 | 2020 |
| Causal rule ensemble: Interpretable inference of heterogeneous treatment effects K Lee, FJ Bargagli-Stoffi, F Dominici arXiv preprint arXiv:2009.09036, 2020 | 23 | 2020 |
| Heterogeneous causal effects with imperfect compliance: a Bayesian machine learning approach FJ Bargagli-Stoffi, K De-Witte, G Gnecco arXiv preprint arXiv:1905.12707, 2019 | 17 | 2019 |
| Estimating heterogeneous causal effects in the presence of irregular assignment mechanisms FJ Bargagli Stoffi, G Gnecco 2018 IEEE 5th International Conference on Data Science and Advanced …, 2018 | 16 | 2018 |
| Supervised learning for the prediction of firm dynamics FJ Bargagli-Stoffi, J Niederreiter, M Riccaboni Data Science for Economics and Finance, 19-41, 2021 | 14 | 2021 |
| Heterogeneous Treatment and Spillover Effects under Clustered Network Interference FJ Bargagli Stoffi, C Tortú, L Forastiere arXiv preprint arXiv:2008.00707, 2020 | 11 | 2020 |
| Exposure to unconventional oil and gas development and all-cause mortality in Medicare beneficiaries L Li, F Dominici, AJ Blomberg, FJ Bargagli-Stoffi, JD Schwartz, BA Coull, ... Nature Energy 7 (2), 177-185, 2022 | 5 | 2022 |
| Machine Learning for Zombie Hunting: Predicting Distress from Firms' Accounts and Missing Values F Bargagli Stoffi, M Riccaboni, A Rungi | 5* | 2022 |
| From controlled to undisciplined data: estimating causal effects in the era of data science using a potential outcome framework F Dominici, FJ Bargagli-Stoffi, F Mealli Harvard Data Science Review, 2022 | 4 | 2022 |
| Simple Models in Complex Worlds: Occam’s Razor and Statistical Learning Theory FJ Bargagli Stoffi, G Cevolani, G Gnecco Minds and Machines 32 (1), 13-42, 2022 | 2 | 2022 |
| Should Simplicity Be Always Preferred to Complexity in Supervised Machine Learning? F Bargagli-Stoffi, G Cevolani, G Gnecco International Conference on Machine Learning, Optimization, and Data Science …, 2020 | 2 | 2020 |
| Essays on applied machine learning FJ Bargagli Stoffi IMT School for Advanced Studies Lucca, 2020 | 1 | 2020 |
| Causal Inference and Machine Learning approaches to discover de novo sub-populations with heterogeneous air pollution health effects F Dominici, K Lee, F Bargagli Stoffi ISEE Conference Abstracts 2021 (1), 2021 | | 2021 |
| Assessing the Value of Echocardiography in the Absence of Randomized Trials: How Analytic Techniques from Causal Inference Can Fill the Gap JH Wasfy, FJ Bargagli-Stoffi Journal of the American Society of Echocardiography, 2021 | | 2021 |
| Assessing Sensitivity of Machine Learning Predictions. A Novel Toolbox with an Application to Financial Literacy FJ Bargagli Stoffi, K De Beckker, JE Maldonado, K De Witte arXiv preprint arXiv:2102.04382, 2021 | | 2021 |
| The effectiveness of the GOK policy M Smet, G D'Inverno, H Tierens, K De Witte, F Bargagli Stoffi Politeia, 2021 | | 2021 |
