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2020 – today
- 2024
[c4]Julia Yang, Alina Jade Barnett, Jon Donnelly, Satvik Kishore, Jerry Fang, Fides Regina Schwartz, Chaofan Chen, Joseph Y. Lo, Cynthia Rudin:
FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for Classification of Mass Margins in Digital Mammography. CVPR Workshops 2024: 5003-5009- [c3]Cynthia Rudin, Chudi Zhong, Lesia Semenova, Margo I. Seltzer, Ronald Parr, Jiachang Liu, Srikar Katta, Jon Donnelly, Harry Chen, Zachery Boner:
Position: Amazing Things Come From Having Many Good Models. ICML 2024 - [i8]Julia Yang, Alina Jade Barnett
, Jon Donnelly, Satvik Kishore, Jerry Fang, Fides Regina Schwartz, Chaofan Chen, Joseph Y. Lo, Cynthia Rudin:
FPN-IAIA-BL: A Multi-Scale Interpretable Deep Learning Model for Classification of Mass Margins in Digital Mammography. CoRR abs/2406.06386 (2024) - [i7]Frank Willard, Luke Moffett, Emmanuel Mokel, Jon Donnelly, Stark Guo, Julia Yang, Giyoung Kim, Alina Jade Barnett, Cynthia Rudin:
This Looks Better than That: Better Interpretable Models with ProtoPNeXt. CoRR abs/2406.14675 (2024) - [i6]Cynthia Rudin, Chudi Zhong, Lesia Semenova, Margo I. Seltzer, Ronald Parr, Jiachang Liu, Srikar Katta, Jon Donnelly, Harry Chen, Zachery Boner:
Amazing Things Come From Having Many Good Models. CoRR abs/2407.04846 (2024) - [i5]Chiyu Ma, Jon Donnelly, Wenjun Liu, Soroush Vosoughi, Cynthia Rudin, Chaofan Chen:
Interpretable Image Classification with Adaptive Prototype-based Vision Transformers. CoRR abs/2410.20722 (2024) - [i4]Hayden McTavish, Jon Donnelly, Margo I. Seltzer, Cynthia Rudin:
Interpretable Generalized Additive Models for Datasets with Missing Values. CoRR abs/2412.02646 (2024) - 2023
- [j1]Jon Donnelly, Peter Stechlinski:
Analyzing the Influence of Agents in Trust Networks: Applying Nonsmooth Eigensensitivity Theory to a Graph Centrality Problem. SIAM J. Matrix Anal. Appl. 44(3): 1271-1298 (2023) - [c2]Jon Donnelly, Srikar Katta, Cynthia Rudin, Edward P. Browne:
The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance. NeurIPS 2023 - [i3]Jon Donnelly, Srikar Katta, Cynthia Rudin, Edward P. Browne:
The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance. CoRR abs/2309.13775 (2023) - [i2]Dennis Tang, Frank Willard, Ronan Tegerdine, Luke Triplett, Jon Donnelly, Luke Moffett, Lesia Semenova, Alina Jade Barnett, Jin Jing, Cynthia Rudin, M. Brandon Westover:
ProtoEEGNet: An Interpretable Approach for Detecting Interictal Epileptiform Discharges. CoRR abs/2312.10056 (2023) - 2022
- [c1]Jon Donnelly, Alina Jade Barnett, Chaofan Chen:
Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes. CVPR 2022: 10255-10265 - 2021
- [i1]Jon Donnelly, Alina Jade Barnett, Chaofan Chen:
Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes. CoRR abs/2111.15000 (2021)
Coauthor Index
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