| FLAME: A fast large-scale almost matching exactly approach to causal inference T Wang, M Morucci, MU Awan, Y Liu, S Roy, C Rudin, A Volfovsky Journal of Machine Learning Research 22 (31), 1-41, 2021 | 68 | 2021 |
| All change in the house? The profile of candidates and MPs in the 2015 British general election C Lamprinakou, M Morucci, R Campbell, J van Heerde-Hudson Parliamentary Affairs 70 (2), 207-232, 2017 | 49 | 2017 |
| Almost-matching-exactly for treatment effect estimation under network interference U Awan, M Morucci, V Orlandi, S Roy, C Rudin, A Volfovsky International conference on artificial intelligence and statistics, 3252-3262, 2020 | 20 | 2020 |
| Adaptive hyper-box matching for interpretable individualized treatment effect estimation M Morucci, V Orlandi, S Roy, C Rudin, A Volfovsky Conference on Uncertainty in Artificial Intelligence, 1089-1098, 2020 | 15 | 2020 |
| Hypothesis tests that are robust to choice of matching method M Morucci, M Noor-E-Alam, C Rudin arXiv preprint arXiv:1812.02227, 2018 | 10 | 2018 |
| Model complexity for supervised learning: why simple models almost always work best, and why it matters for applied research M Morucci, A Spirling Department of Political Science, Michigan State University, 2024 | 9 | 2024 |
| Sudeepa Roy, Cynthia Rudin, and Alexander Volfovsky. Adaptive hyper-box matching for interpretable individualized treatment effect estimation M Morucci, V Orlandi Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial …, 2020 | 9 | 2020 |
| Antipolitical class bias in corruption sentencing L Doria Vilaça, M Morucci, V Paniagua American Journal of Political Science 69 (2), 701-717, 2025 | 7 | 2025 |
| Measurement That Matches Theory: Theory-Driven Identification in Item Response Theory Models M Morucci, MJ Foster, K Webster, SJ Lee, DA Siegel American Political Science Review 119 (2), 727-745, 2025 | 6 | 2025 |
| A double machine learning approach to combining experimental and observational data M Morucci, V Orlandi, H Parikh, S Roy, C Rudin, A Volfovsky CoRR, 2023 | 6 | 2023 |
| A robust approach to quantifying uncertainty in matching problems of causal inference M Morucci, M Noor-E-Alam, C Rudin INFORMS Journal on Data Science 1 (2), 156-171, 2022 | 6 | 2022 |
| A double machine learning approach to combining experimental and observational data H Parikh, M Morucci, V Orlandi, S Roy, C Rudin, A Volfovsky arXiv preprint arXiv:2307.01449, 2023 | 4 | 2023 |
| Interpretable almost matching exactly with instrumental variables MU Awan, Y Liu, M Morucci, S Roy, C Rudin, A Volfovsky Uncertainty in Artificial Intelligence, 1116-1126, 2020 | 4 | 2020 |
| dame-flame: A python library providing fast interpretable matching for causal inference NR Gupta, V Orlandi, CR Chang, T Wang, M Morucci, P Dey, TJ Howell, ... arXiv preprint arXiv:2101.01867, 2021 | 3 | 2021 |
| Matching Bounds: How Choice of Matching Algorithm Impacts Treatment Effects Estimates and What to Do about It M Morucci, C Rudin arXiv preprint arXiv:2009.02776, 2020 | 3 | 2020 |
| Multi-task learning improves performance in deep argument mining models A Farzam, S Shekhar, I Mehlhaff, M Morucci Proceedings of the 11th Workshop on Argument Mining (ArgMining 2024), 46-58, 2024 | 2 | 2024 |
| Matched machine learning: A generalized framework for treatment effect inference with learned metrics M Morucci, C Rudin, A Volfovsky arXiv preprint arXiv:2304.01316, 2023 | 2 | 2023 |
| Measurement that matches theory: theory-driven identification in IRT models M Morucci, M Foster, K Webster, SJ Lee, D Siegel arXiv preprint arXiv:2111.11979, 2021 | 1 | 2021 |
| A robust approach to quantifying uncertainty in matching problems of causal inference M Morucci, C Rudin arXiv preprint arXiv:1812.02227, 2018 | 1 | 2018 |
| Shuffling the House of Cards? The Profile of Candidates and MPs in the 2015 British General Election C Lamprinakou, M Morucci, R Campbell, J van Heerde-Hudson British General Election: Transition or Crisis?’2 September 2015, University …, 2015 | 1 | 2015 |
