| Explaining data-driven decisions made by AI systems: the counterfactual approach C Fernández-Loría, F Provost, X Han arXiv preprint arXiv:2001.07417, 2020 | 93 | 2020 |
| Causal decision making and causal effect estimation are not the same… and why it matters C Fernández-Loría, F Provost INFORMS Journal on Data Science 1 (1), 4-16, 2022 | 40 | 2022 |
| Causal classification: Treatment effect estimation vs. outcome prediction C Fernández-Loría, F Provost Journal of Machine Learning Research 23 (59), 1-35, 2022 | 36* | 2022 |
| Counterfactual explanations for data-driven decisions C Fernandez, F Provost, X Han | 17 | 2019 |
| A comparison of methods for treatment assignment with an application to playlist generation C Fernández-Loría, F Provost, J Anderton, B Carterette, P Chandar Information Systems Research 34 (2), 786-803, 2023 | 14 | 2023 |
| Evolution of referrals over customers’ life cycle: Evidence from a ride-sharing platform C Fernández-Loría, MC Cohen, A Ghose Information Systems Research 34 (2), 698-720, 2023 | 8 | 2023 |
| Causal decision making and causal effect estimation are not the same... and why it matters C Fernández-Loría, F Provost arXiv preprint arXiv:2104.04103, 2021 | 7 | 2021 |
| Observational vs experimental data when making automated decisions using machine learning C Fernández-Loría, F Provost NYU Stern School of Business, 2019 | 7 | 2019 |
| Methods for individual treatment assignment: An application and comparison for playlist generation C Fernandez, F Provost, J Anderton, B Carterette, P Chandar arXiv preprint arXiv:2004.11532, 2020 | 4 | 2020 |
| Combining observational and experimental data to improve large-scale decision-making C Fernández-Loría, F Provost | 4 | 2020 |
| Empirical analysis of referrals in ride-sharing M Cohen, C Fernández, A Ghose Available at SSRN, 2019 | 3 | 2019 |
| Rejoinder to “Causal Decision Making and Causal Effect Estimation Are Not the Same… and Why It Matters” C Fernández-Loría, F Provost INFORMS Journal on Data Science 1 (1), 23-26, 2022 | 2 | 2022 |
| Learning the Ranking of Causal Effects with Confounded Data. C Fernández-Loría, J Loría CoRR, 2022 | 2 | 2022 |
| Learning to Rank by Causal Effects Without Data to Accurately Estimate Causal Effects C Fernández-Loría, J Loría arXiv preprint arXiv:2206.12532, 2022 | | 2022 |
| Counterfactual explanations for data-driven decisions CM Fernandez Loria, F Provost, X Han | | 2019 |
| Causal Classification: Treatment Effect vs. Outcome Estimation C Fernandez, F Provost | | 2018 |
| Caracterización de las propiedades fisicoquímicas y funcionales de la pulpa de lulo del injerto entre las variedades Solanum quitoense y Solanum hietum como herramienta para … C Fernandez, O Osorio, A Hurtado-Benavides | | 2011 |
| Determinación de las condiciones óptimas en el secado del cilantro cimarrón (Erynguium foetidum l.) para la conservación de sus caracteristicas organolépticas y componentes … C Fernandez, O Osorio, A Hurtado-Benavides | | 2011 |
| Relationship between drying and breaking of kernels in six Costa Rican rice mills (1987-1988 crop). M Zeledón, C Fernández | | 1991 |
Foster ProvostProfessor, New York UniversityVerified email at stern.nyu.edu
