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Falco J. Bargagli Stoffi
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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
242020
Causal rule ensemble: Interpretable inference of heterogeneous treatment effects
K Lee, FJ Bargagli-Stoffi, F Dominici
arXiv preprint arXiv:2009.09036, 2020
232020
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
172019
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 Advancedá…, 2018
162018
Supervised learning for the prediction of firm dynamics
FJ Bargagli-Stoffi, J Niederreiter, M Riccaboni
Data Science for Economics and Finance, 19-41, 2021
142021
Heterogeneous Treatment and Spillover Effects under Clustered Network Interference
FJ Bargagli Stoffi, C Tort˙, L Forastiere
arXiv preprint arXiv:2008.00707, 2020
112020
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
52022
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
42022
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
22022
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 Scienceá…, 2020
22020
Essays on applied machine learning
FJ Bargagli Stoffi
IMT School for Advanced Studies Lucca, 2020
12020
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
Il sistema al momento non pu˛ eseguire l'operazione. Riprova pi¨ tardi.
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