| This Looks Like That: Deep Learning for Interpretable Image Recognition C Chen, O Li, C Tao, AJ Barnett, J Su, C Rudin Advances in Neural Information Processing Systems 32 (NeurIPS 2019), 2019 | 1413 | 2019 |
| Interpretable machine learning: Fundamental principles and 10 grand challenges C Rudin, C Chen, Z Chen, H Huang, L Semenova, C Zhong Statistics Surveys 16, 1-85, 2022 | 887 | 2022 |
| Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains its Predictions O Li, H Liu, C Chen, C Rudin AAAI Conference on Artificial Intelligence (AAAI 2018), 2018 | 688 | 2018 |
| Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes J Donnelly, AJ Barnett, C Chen Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 135 | 2022 |
| Interpretable Image Recognition with Hierarchical Prototypes P Hase, C Chen, O Li, C Rudin AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2019), 2019 | 135 | 2019 |
| A case-based interpretable deep learning model for classification of mass lesions in digital mammography AJ Barnett, FR Schwartz, C Tao, C Chen, Y Ren, JY Lo, C Rudin Nature Machine Intelligence 3 (12), 1061-1070, 2021 | 128 | 2021 |
| An Interpretable Model with Globally Consistent Explanations for Credit Risk C Chen, K Lin, C Rudin, Y Shaposhnik, S Wang, T Wang NIPS 2018 Workshop on Challenges and Opportunities for AI in Financial …, 2018 | 118 | 2018 |
| A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations C Chen, K Lin, C Rudin, Y Shaposhnik, S Wang, T Wang Decision Support Systems 152, 113647, 2022 | 54 | 2022 |
| An Optimization Approach to Learning Falling Rule Lists C Chen, C Rudin International Conference on Artificial Intelligence and Statistics (AISTATS …, 2018 | 52 | 2018 |
| This Looks Like Those: Illuminating Prototypical Concepts Using Multiple Visualizations C Ma, B Zhao, C Chen, C Rudin Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS …, 2023 | 22 | 2023 |
| Interpretable Mammographic Image Classification using Case-Based Reasoning and Deep Learning AJ Barnett, FR Schwartz, C Tao, C Chen, Y Ren, JY Lo, C Rudin arXiv preprint arXiv:2107.05605, 2021 | 17 | 2021 |
| medna-metadata: an open-source data management system for tracking environmental DNA samples and metadata M Kimble, S Allers, K Campbell, C Chen, LM Jackson, BL King, ... Bioinformatics 38 (19), 4589-4597, 2022 | 6 | 2022 |
| Interpretable deep learning models for better clinician-AI communication in clinical mammography AJ Barnett, V Sharma, N Gajjar, J Fang, F Schwartz, C Chen, JY Lo, ... Medical Imaging 2022: Image Perception, Observer Performance, and Technology …, 2022 | 4 | 2022 |
| Few-shot learning-based generative design of metamaterials with zero Poisson’s ratio X Liu, H Zhao, Y Tang, C Chen, Y Zhu, B Song, Y Li Materials & Design 244, 113224, 2024 | 3 | 2024 |
| Interpretability by Design: New Interpretable Machine Learning Models and Methods C Chen Duke University, 2020 | 3 | 2020 |
| A patient-informed approach to predict iodinated-contrast media enhancement in the liver H Setiawan, C Chen, E Abadi, W Fu, D Marin, F Ria, E Samei European Journal of Radiology 156, 110555, 2022 | 2 | 2022 |
| Interpretable Image Classification with Adaptive Prototype-based Vision Transformers C Ma, J Donnelly, W Liu, S Vosoughi, C Rudin, C Chen The Thirty-eighth Annual Conference on Neural Information Processing Systems …, 2024 | 1 | 2024 |
| FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for Classification of Mass Margins in Digital Mammography J Yang, AJ Barnett, J Donnelly, S Kishore, J Fang, FR Schwartz, C Chen, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 1 | 2024 |
