Donnelly, Jon

9 publications

AAAI 2025 How Your Location Relates to Health: Variable Importance and Interpretable Machine Learning for Environmental and Sociodemographic Data Ishaan Maitra, Raymond Lin, Eric Chen, Jon Donnelly, Sanja Scepanovic, Cynthia Rudin

ICML 2025 Leveraging Predictive Equivalence in Decision Trees Hayden Mctavish, Zachery Boner, Jon Donnelly, Margo Seltzer, Cynthia Rudin

CVPR 2025 Rashomon Sets for Prototypical-Part Networks: Editing Interpretable Models in Real-Time Jon Donnelly, Zhicheng Guo, Alina Jade Barnett, Hayden McTavish, Chaofan Chen, Cynthia Rudin

CVPRW 2024 FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for Classification of Mass Margins in Digital Mammography Julia Yang, Alina Jade Barnett, Jon Donnelly, Satvik Kishore, Jerry Fang, Fides Regina Schwartz, Chaofan Chen, Joseph Y. Lo, Cynthia Rudin

NeurIPS 2024 Interpretable Generalized Additive Models for Datasets with Missing Values Hayden McTavish, Jon Donnelly, Margo Seltzer, Cynthia Rudin

NeurIPS 2024 Interpretable Image Classification with Adaptive Prototype-Based Vision Transformers Chiyu Ma, Jon Donnelly, Wenjun Liu, Soroush Vosoughi, Cynthia Rudin, Chaofan Chen

ICML 2024 Position: Amazing Things Come from Having Many Good Models Cynthia Rudin, Chudi Zhong, Lesia Semenova, Margo Seltzer, Ronald Parr, Jiachang Liu, Srikar Katta, Jon Donnelly, Harry Chen, Zachery Boner

NeurIPS 2023 The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-Based Variable Importance Jon Donnelly, Srikar Katta, Cynthia Rudin, Edward Browne

CVPR 2022 Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes Jon Donnelly, Alina Jade Barnett, Chaofan Chen