---
title: "Cynthia D Rudin — all works — Elamur Research"
description: "All 330 works of Cynthia D Rudin in the Elamur Research library, the most cited first: our summaries where we have them, else the original."
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---
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# Cynthia D Rudin — all works

330 works · page 1 of 4 · 1–100 · [← Cynthia D Rudin](https://md.research.elamur.ai/free/en/authors/cynthia-d-rudin/)

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1. **[Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead](https://md.research.elamur.ai/free/en/papers/rudin-2018-stop-explaining-black-box/) [Nature Machine Intelligence](https://md.research.elamur.ai/free/en/venues/nature-machine-intelligence/)**Cynthia Rudin*2018 · 10,460 citations*
2. **[All Models are Wrong, but Many are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously ↗](https://arxiv.org/abs/1801.01489) arXiv (Cornell University) · no summary yet**Aaron Fisher, Cynthia D Rudin, Francesca Dominici*2018 · 1,155 citations*
3. **[Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model ↗](https://doi.org/10.1214/15-aoas848) The Annals of Applied Statistics · no summary yet**Benjamin Letham et al.*2015 · 783 citations*
4. **[This Looks Like That: Deep Learning for Interpretable Image Recognition ↗](https://arxiv.org/abs/1806.10574) arXiv (Cornell University) · no summary yet**Chaofan Chen et al.*2018 · 590 citations*
5. **[Deep Learning for Case-Based Reasoning Through Prototypes: A Neural Network That Explains Its Predictions ↗](https://doi.org/10.1609/aaai.v32i1.11771) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Oscar Li et al.*2018 · 547 citations*
6. **[PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models ↗](https://doi.org/10.1109/cvpr42600.2020.00251) IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yet**Sachit Menon et al.*2020 · 540 citations*
7. **[The Big Data Newsvendor: Practical Insights from Machine Learning ↗](https://doi.org/10.1287/opre.2018.1757) Operations Research · no summary yet**Gah‐Yi Ban, Cynthia D Rudin*2018 · 508 citations*
8. **[Why Are We Using Black Box Models in AI When We Don’t Need To? A Lesson From An Explainable AI Competition ↗](https://doi.org/10.1162/99608f92.5a8a3a3d) Harvard Data Science Review · no summary yet**Cynthia D Rudin, Joanna Radin*2019 · 437 citations*
9. **[Supersparse linear integer models for optimized medical scoring systems ↗](https://doi.org/10.1007/s10994-015-5528-6) Machine Learning · no summary yet**Berk Ustun, Cynthia D Rudin*2015 · 335 citations*
10. **[Concept whitening for interpretable image recognition ↗](https://doi.org/10.1038/s42256-020-00265-z) Nature Machine Intelligence · no summary yet**Zhi Chen, Yijie Bei, Cynthia D Rudin*2020 · 294 citations*
11. **[Machine Learning for the New York City Power Grid ↗](https://doi.org/10.1109/tpami.2011.108) IEEE Transactions on Pattern Analysis and Machine Intelligence · no summary yet**Cynthia D Rudin et al.*2011 · 263 citations*
12. **[Understanding How Dimension Reduction Tools Work: An Empirical Approach to Deciphering t-SNE, UMAP, TriMAP, and PaCMAP for Data Visualization ↗](https://arxiv.org/abs/2012.04456) arXiv (Cornell University) · no summary yet**Yingfan Wang et al.*2020 · 252 citations*
13. [**Arabic Morphological Tagging, Diacritization, and Lemmatization Using Lexeme Models and Feature Ranking**Ryan Roth, Owen Rambow, Nizar Habash, et al.*Semitic languages · 217 citations*](https://md.research.elamur.ai/free/en/papers/roth-2008-arabic-morphological-tagging-diacritization-lemmatization/)
14. **[A Shared Vision for Machine Learning in Neuroscience ↗](https://doi.org/10.1523/jneurosci.0508-17.2018) Journal of Neuroscience · no summary yet**Mai-Anh T. Vu et al.*2018 · 190 citations*
15. **[The Age of Secrecy and Unfairness in Recidivism Prediction ↗](https://doi.org/10.1162/99608f92.6ed64b30) Harvard Data Science Review · no summary yet**Cynthia D Rudin, Caroline Wang, Beau Coker*2018 · 183 citations*
16. **[Applied machine learning as a driver for polymeric biomaterials design ↗](https://doi.org/10.1038/s41467-023-40459-8) Nature Communications · no summary yet**Samantha M. McDonald et al.*2023 · 167 citations*
17. **[Learning classification models of cognitive conditions from subtle behaviors in the digital Clock Drawing Test ↗](https://doi.org/10.1007/s10994-015-5529-5) Machine Learning · no summary yet**William Souillard‐Mandar et al.*2015 · 166 citations*
18. **[A case-based interpretable deep learning model for classification of mass lesions in digital mammography ↗](https://doi.org/10.1038/s42256-021-00423-x) Nature Machine Intelligence · no summary yet**Alina Jade Barnett et al.*2021 · 164 citations*
19. **[Interpretable Classification Models for Recidivism Prediction ↗](https://doi.org/10.1111/rssa.12227) Journal of the Royal Statistical Society Series A (Statistics in Society) · no summary yet**Jiaming Zeng, Berk Ustun, Cynthia D Rudin*2016 · 162 citations*
20. **[Towards a comprehensive evaluation of dimension reduction methods for transcriptomic data visualization ↗](https://doi.org/10.1038/s42003-022-03628-x) Communications Biology · no summary yet**Haiyang Huang et al.*2022 · 148 citations*
21. **[Interpretable Image Recognition with Hierarchical Prototypes ↗](https://doi.org/10.1609/hcomp.v7i1.5265) Proceedings of the AAAI Conference on Human Computation and Crowdsourcing · no summary yet**Peter Hase et al.*2019 · 131 citations*
22. **[The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification ↗](http://hdl.handle.net/1721.1/91918) arXiv (Cornell University) · no summary yet**Been Kim, Cynthia D Rudin, Julie Shah*2014 · 131 citations*
23. **[Optimized Scoring Systems: Toward Trust in Machine Learning for Healthcare and Criminal Justice ↗](https://doi.org/10.1287/inte.2018.0957) INFORMS Journal on Applied Analytics · no summary yet**Cynthia D Rudin, Berk Ustun*2018 · 122 citations*
24. **[Learning to Detect Patterns of Crime ↗](https://doi.org/10.1007/978-3-642-40994-3_33) Lecture notes in computer science · no summary yet**Tong Wang et al.*2013 · 120 citations*
25. **[Learning Certifiably Optimal Rule Lists for Categorical Data ↗](https://arxiv.org/abs/1704.01701) arXiv (Cornell University) · no summary yet**Elaine Lee Angelino et al.*2017 · 118 citations*
26. **[Machine learning for science and society ↗](https://doi.org/10.1007/s10994-013-5425-9) Machine Learning · no summary yet**Cynthia D Rudin, Kiri L. Wagstaff*2013 · 116 citations*
27. **[In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction ↗](https://doi.org/10.1007/s10940-022-09545-w) Journal of Quantitative Criminology · no summary yet**Caroline Wang et al.*2022 · 106 citations*
28. **[Why black box machine learning should be avoided for high-stakes decisions, in brief ↗](https://doi.org/10.1038/s43586-022-00172-0) Nature Reviews Methods Primers · no summary yet**Cynthia D Rudin*2022 · 105 citations*
29. **[Learning Certifiably Optimal Rule Lists ↗](https://doi.org/10.1145/3097983.3098047) ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · no summary yet**Elaine Lee Angelino et al.*2017 · 105 citations*
30. **[On the Existence of Simpler Machine Learning Models ↗](https://doi.org/10.1145/3531146.3533232) ACM Conference on Fairness, Accountability, and Transparency (FAccT) · no summary yet**Lesia Semenova, Cynthia D Rudin, Ronald Parr*2019 · 99 citations*
31. **[The Dynamics of AdaBoost: Cyclic Behavior and Convergence of Margins ↗](https://doi.org/10.5555/1005332.1044712) no summary yet**Cynthia D Rudin, Ingrid C. Daubechies, Robert E. Schapire*2004 · 89 citations*
32. **[Margin-Based Ranking Meets Boosting in the Middle ↗](https://doi.org/10.1007/11503415_5) Lecture notes in computer science · no summary yet**Cynthia D Rudin et al.*2005 · 69 citations*
33. **[An Interpretable Model with Globally Consistent Explanations for Credit Risk ↗](https://arxiv.org/abs/1811.12615) arXiv (Cornell University) · no summary yet**Chaofan Chen et al.*2018 · 65 citations*
34. **[AsymMirai: Interpretable Mammography-based Deep Learning Model for 1–5-year Breast Cancer Risk Prediction ↗](https://doi.org/10.1148/radiol.232780) Radiology · no summary yet**Jon P. Donnelly et al.*2024 · 63 citations*
35. **[Generalized and Scalable Optimal Sparse Decision Trees ↗](https://arxiv.org/abs/2006.08690) arXiv (Cornell University) · no summary yet**Lin, Jimmy et al.*2020 · 61 citations*
36. **[A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations ↗](https://doi.org/10.1016/j.dss.2021.113647) Decision Support Systems · no summary yet**Chaofan Chen et al.*2021 · 60 citations*
37. **[Exploring the cloud of variable importance for the set of all good models ↗](https://doi.org/10.1038/s42256-020-00264-0) Nature Machine Intelligence · no summary yet**Jiayun Dong, Cynthia D Rudin*2020 · 59 citations*
38. **[A process for predicting manhole events in Manhattan ↗](https://doi.org/10.1007/s10994-009-5166-y) Machine Learning · no summary yet**Cynthia D Rudin et al.*2010 · 58 citations*
39. **[Ranking with a P-Norm Push ↗](https://doi.org/10.1007/11776420_43) Lecture notes in computer science · no summary yet**Cynthia D Rudin*2006 · 57 citations*
40. **[Learning Optimized Risk Scores ↗](https://arxiv.org/abs/1610.00168) arXiv (Cornell University) · no summary yet**Berk Ustun, Cynthia D Rudin*2016 · 56 citations*
41. **[Learning customized and optimized lists of rules with mathematical programming ↗](https://doi.org/10.1007/s12532-018-0143-8) Mathematical Programming Computation · no summary yet**Cynthia D Rudin, Şeyda Ertekin*2018 · 55 citations*
42. **[Learning Cost-Effective and Interpretable Treatment Regimes ↗](https://openalex.org/W2645304696) International Conference on Artificial Intelligence and Statistics · no summary yet**Himabindu Lakkaraju, Cynthia D Rudin*2017 · 53 citations*
43. **[Optimized Risk Scores ↗](https://doi.org/10.1145/3097983.3098161) ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · no summary yet**Berk Ustun, Cynthia D Rudin*2017 · 53 citations*
44. **[Sequential event prediction ↗](https://doi.org/10.1007/s10994-013-5356-5) Machine Learning · no summary yet**Benjamin Letham, Cynthia D Rudin, David Madigan*2013 · 53 citations*
45. **[Reactive point processes: A new approach to predicting power failures in underground electrical systems ↗](https://doi.org/10.1214/14-aoas789) The Annals of Applied Statistics · no summary yet**Şeyda Ertekin, Cynthia D Rudin, Tyler H. McCormick*2015 · 52 citations*
46. **[Online coordinate boosting ↗](https://doi.org/10.1109/iccvw.2009.5457454) arXiv:0810.4553 · no summary yet**Raphael A. Pelossof et al.*2009 · 52 citations*
47. **[Interpretable algorithmic forensics ↗](https://doi.org/10.1073/pnas.2301842120) Proceedings of the National Academy of Sciences · no summary yet**Brandon L. Garrett, Cynthia D Rudin*2023 · 48 citations*
48. **[Bayesian Rule Sets for Interpretable Classification ↗](https://doi.org/10.1109/icdm.2016.0171) Proceedings · no summary yet**Tong Wang et al.*2016 · 46 citations*
49. **[Fast Sparse Decision Tree Optimization via Reference Ensembles ↗](https://doi.org/10.1609/aaai.v36i9.21194) Proceedings of the AAAI Conference on Artificial Intelligence · no summary yet**Hayden McTavish et al.*2022 · 45 citations*
50. **[Box drawings for learning with imbalanced data ↗](https://doi.org/10.1145/2623330.2623648) ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) · no summary yet**Siong Thye Goh, Cynthia D Rudin*2014 · 45 citations*
51. **[Bayesian hierarchical rule modeling for predicting medical conditions ↗](https://doi.org/10.1214/11-aoas522) The Annals of Applied Statistics · no summary yet**Tyler H. McCormick, Cynthia D Rudin, David Madigan*2012 · 42 citations*
52. **[Prediction of tensile performance for 3D printed photopolymer gyroid lattices using structural porosity, base material properties, and machine learning ↗](https://doi.org/10.1016/j.matdes.2023.112126) Materials & Design · no summary yet**Jacob Peloquin et al.*2023 · 40 citations*
53. **[Metaphor Detection Using Contextual Word Embeddings From Transformers ↗](https://aclanthology.org/2020.figlang-1.34/) Proceedings of the Second Workshop on Figurative Language Processing · no summary yet**Jerry Liu et al.*2020 · 39 citations*
54. **[A Transformer Approach to Contextual Sarcasm Detection in Twitter](https://md.research.elamur.ai/free/en/papers/gregory-2020-transformer-approach-contextual-sarcasm-detection/) [Workshop on Figurative Language Processing](https://md.research.elamur.ai/free/en/venues/figlang/)**Hunter Gregory, Steven Li, Pouya Mohammadi, et al.*2020 · 38 citations*
55. **[Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application to Credit-Risk Evaluation ↗](https://doi.org/10.2139/ssrn.3395422) SSRN Electronic Journal · no summary yet**Cynthia D Rudin, Yaron Shaposhnik*2019 · 38 citations*
56. **[Exploring the Whole Rashomon Set of Sparse Decision Trees ↗](https://arxiv.org/abs/2209.08040) PubMed · no summary yet**Rui Xin et al.*2022 · 37 citations*
57. **[The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to Be More Effective at Data Analysis ↗](https://doi.org/10.1287/educ.2019.0200) arXiv:1906.01998 · no summary yet**Cynthia D Rudin, David Carlson*2019 · 37 citations*
58. **[Discovery with Data: Leveraging Statistics with Computer Science to Transform Science and Society ↗](https://openalex.org/W2276442554) no summary yet**Cynthia D Rudin et al.*2014 · 35 citations*
59. **[The rate of convergence of AdaBoost ↗](https://doi.org/10.5555/2567709.2567735) Journal of Machine Learning Research · no summary yet**Indraneel Mukherjee, Cynthia D Rudin, Robert E. Schapire*2013 · 35 citations*
60. **[How to see hidden patterns in metamaterials with interpretable machine learning ↗](https://doi.org/10.1016/j.eml.2022.101895) Extreme Mechanics Letters · no summary yet**Zhi Chen et al.*2022 · 34 citations*
61. **[New Techniques for Preserving Global Structure and Denoising with Low Information Loss in Single-Image Super-Resolution ↗](https://doi.org/10.1109/cvprw.2018.00132) IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · no summary yet**Yijie Bei et al.*2018 · 34 citations*
62. **[Or's of And's for Interpretable Classification, with Application to Context-Aware Recommender Systems ↗](https://arxiv.org/abs/1504.07614) arXiv (Cornell University) · no summary yet**Tong Wang et al.*2015 · 32 citations*
63. **[On combining machine learning with decision making ↗](https://doi.org/10.1007/s10994-014-5459-7) Machine Learning · no summary yet**Theja Tulabandhula, Cynthia D Rudin*2014 · 32 citations*
64. **[Finding Patterns with a Rotten Core: Data Mining for Crime Series with Cores ↗](https://doi.org/10.1089/big.2014.0021) Big Data · no summary yet**Tong Wang et al.*2014 · 30 citations*
65. **[From Artificial Intelligence (AI) to Intelligence Augmentation (IA): Design Principles, Potential Risks, and Emerging Issues ↗](https://doi.org/10.17705/1thci.00185) AIS Transactions on Human-Computer Interaction · no summary yet**Lina Zhou et al.*2023 · 29 citations*
66. **[Optimal Sparse Decision Trees ↗](https://arxiv.org/abs/1904.12847) arXiv (Cornell University) · no summary yet**Xiyang Hu, Cynthia D Rudin, Margo Seltzer*2019 · 29 citations*
67. **[FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference ↗](https://arxiv.org/abs/1707.06315) arXiv (Cornell University) · no summary yet**Tianyu Wang et al.*2017 · 29 citations*
68. **[Analytics for Power Grid Distribution Reliability in New York City ↗](https://doi.org/10.1287/inte.2014.0748) INFORMS Journal on Applied Analytics · no summary yet**Cynthia D Rudin et al.*2014 · 29 citations*
69. **[Methods and Models for Interpretable Linear Classification ↗](https://arxiv.org/abs/1405.4047) arXiv (Cornell University) · no summary yet**Berk Ustun, Cynthia D Rudin*2014 · 28 citations*
70. **[Learning to Predict the Wisdom of Crowds ↗](https://arxiv.org/abs/1204.3611) arXiv (Cornell University) · no summary yet**Şeyda Ertekin, Haym Hirsh, Cynthia D Rudin*2012 · 28 citations*
71. **[Analysis of boosting algorithms using the smooth margin function ↗](https://doi.org/10.1214/009053607000000785) The Annals of Statistics · no summary yet**Cynthia D Rudin, Robert E. Schapire, Ingrid C. Daubechies*2007 · 28 citations*
72. **[Robust Optimization using Machine Learning for Uncertainty Sets ↗](https://arxiv.org/abs/1407.1097) arXiv (Cornell University) · no summary yet**Theja Tulabandhula, Cynthia D Rudin*2014 · 26 citations*
73. **[Supersparse Linear Integer Models for Interpretable Classification ↗](https://arxiv.org/abs/1306.6677) arXiv (Cornell University) · no summary yet**Berk Ustun, Stefano Tracà, Cynthia D Rudin*2013 · 25 citations*
74. **[SiamQuality: a ConvNet-based foundation model for photoplethysmography signals ↗](https://doi.org/10.1088/1361-6579/ad6747) Physiological Measurement · no summary yet**Cheng Ding et al.*2024 · 24 citations*
75. **[TimberTrek: Exploring and Curating Sparse Decision Trees with Interactive Visualization ↗](https://doi.org/10.1109/vis54862.2022.00021) IEEE Visualization and Visual Analytics (VIS) · no summary yet**Zijie J. Wang et al.*2022 · 24 citations*
76. **[Detecting patterns of crime with series finder ↗](https://openalex.org/W2195066712) National Conference on Artificial Intelligence · no summary yet**Tong Wang et al.*2013 · 23 citations*
77. **[Re-Ranking Algorithms for Name Tagging ↗](https://aclanthology.org/W06-3607/) Proceedings of the Workshop on Computationally Hard Problems and Joint Inference in Speech and Language Processing · no summary yet**Heng Ji, Cynthia Rudin, Ralph Grishman*2006 · 23 citations*
78. **[Boosting Based on a Smooth Margin ↗](https://doi.org/10.1007/978-3-540-27819-1_35) Lecture notes in computer science · no summary yet**Cynthia D Rudin, Robert E. Schapire, Ingrid C. Daubechies*2004 · 23 citations*
79. **[FasterRisk: Fast and Accurate Interpretable Risk Scores ↗](https://doi.org/10.52202/068431-1291) neural information processing systems · no summary yet**Jiachang Liu et al.*2022 · 22 citations*
80. **[Integrated Single-cell Multiomic Analysis of HIV Latency Reversal Reveals Novel Regulators of Viral Reactivation ↗](https://doi.org/10.1093/gpbjnl/qzae003) Genomics Proteomics & Bioinformatics · no summary yet**Manickam Ashokkumar et al.*2024 · 20 citations*
81. **[A Theory of Statistical Inference for Ensuring the Robustness of Scientific Results ↗](https://doi.org/10.1287/mnsc.2020.3818) Management Science · no summary yet**Beau Coker, Cynthia D Rudin, Gary King*2018 · 20 citations*
82. **[Playing Codenames with Language Graphs and Word Embeddings ↗](https://doi.org/10.1613/jair.1.12665) Journal of Artificial Intelligence Research · no summary yet**Divya Koyyalagunta et al.*2021 · 19 citations*
83. **[Sparse learned kernels for interpretable and efficient medical time series processing ↗](https://doi.org/10.1038/s42256-024-00898-4) Nature Machine Intelligence · no summary yet**Sully F. Chen et al.*2024 · 18 citations*
84. **[Uncertainty quantification of acoustic metamaterial bandgaps with stochastic material properties and geometric defects ↗](https://doi.org/10.1016/j.compstruc.2024.107511) Computers & Structures · no summary yet**Han Zhang et al.*2024 · 18 citations*
85. **[An Optimization Approach to Learning Falling Rule Lists ↗](https://arxiv.org/abs/1710.02572) arXiv (Cornell University) · no summary yet**Chaofan Chen, Cynthia D Rudin*2017 · 18 citations*
86. **[Falling Rule Lists ↗](https://openalex.org/W2964134873) International Conference on Artificial Intelligence and Statistics · no summary yet**Fulton Wang, Cynthia D Rudin*2015 · 18 citations*
87. **[Ethical Implementation of Artificial Intelligence to Select Embryos in In Vitro Fertilization ↗](https://doi.org/10.1145/3461702.3462589) Proceedings of the AAAI/ACM Conference on AI Ethics and Society · no summary yet**Michael Anis Mihdi Afnan et al.*2021 · 17 citations*
88. **[Causal Falling Rule Lists ↗](https://arxiv.org/abs/1510.05189) arXiv (Cornell University) · no summary yet**Fulton Wang, Cynthia D Rudin*2015 · 17 citations*
89. **[Equilibrium island ridge arrays in strained solid films ↗](https://doi.org/10.1063/1.371556) Journal of Applied Physics · no summary yet**Cynthia D Rudin, Brian J. Spencer*1999 · 17 citations*
90. **[Interpretable Image Classification with Adaptive Prototype-based Vision Transformers ↗](https://doi.org/10.52202/079017-1312) neural information processing systems · no summary yet**Chiyu Ma et al.*2024 · 16 citations*
91. **[Amazing Things Come From Having Many Good Models ↗](https://arxiv.org/abs/2407.04846) arXiv (Cornell University) · no summary yet**Cynthia D Rudin et al.*2024 · 16 citations*
92. **[In Pursuit of Interpretable, Fair and Accurate Machine Learning for Criminal Recidivism Prediction ↗](https://arxiv.org/abs/2005.04176) arXiv (Cornell University) · no summary yet**Wang, Caroline et al.*2020 · 16 citations*
93. **[Interpretable Almost-Exact Matching for Causal Inference. ↗](https://www.ncbi.nlm.nih.gov/pmc/articles/6563929) PubMed · no summary yet**Awa Dieng et al.*2019 · 16 citations*
94. **[Growing a list ↗](https://doi.org/10.1007/s10618-013-0329-7) Data Mining and Knowledge Discovery · no summary yet**Benjamin Letham, Cynthia D Rudin, Katherine Heller*2013 · 16 citations*
95. **[Data quality assurance and performance measurement of data mining for preventive maintenance of power grid ↗](https://doi.org/10.1145/2018673.2018679) no summary yet**Leon Wu et al.*2011 · 16 citations*
96. **[This Looks Like Those: Illuminating Prototypical Concepts Using Multiple Visualizations ↗](https://doi.org/10.52202/075280-1704) neural information processing systems · no summary yet**Chiyu Ma et al.*2023 · 15 citations*
97. **[IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography ↗](https://arxiv.org/abs/2103.12308) arXiv (Cornell University) · no summary yet**Alina Jade Barnett et al.*2021 · 15 citations*
98. **[A Robust Approach to Quantifying Uncertainty in Matching Problems of Causal Inference ↗](https://doi.org/10.1287/ijds.2022.0020) INFORMS Journal on Data Science · no summary yet**Marco Morucci, Md. Noor‐E‐Alam, Cynthia D Rudin*2018 · 15 citations*
99. **[Scalable Bayesian Rule Lists ↗](https://arxiv.org/abs/1602.08610) arXiv (Cornell University) · no summary yet**Hongyu Yang, Cynthia D Rudin, Margo Seltzer*2016 · 15 citations*
100. **[Learning Optimized Or's of And's ↗](https://arxiv.org/abs/1511.02210) arXiv (Cornell University) · no summary yet**Tong Wang, Cynthia D Rudin*2015 · 15 citations*

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