| 2025 | AAAI | Pseudo Informative Episode Construction for Few-Shot Class-Incremental Learning. | Chaofan Chen, Xiaoshan Yang, Changsheng Xu |
| 2025 | CVPR | 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 |
| 2024 | CVPR | 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 |
| 2024 | IJCNN | Semi-supervised Online Elastic Stochastic Configuration Network to Deal with Concept Drift and Class Imbalance in Data Streams. | Chaofan Chen, Wenhao Zhong, Kezhong Lu |
| 2023 | CVPR | Active Exploration of Multimodal Complementarity for Few-Shot Action Recognition. | Yuyang Wanyan, Xiaoshan Yang, Chaofan Chen, Changsheng Xu |
| 2022 | CVPR | Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes. | Jon Donnelly, Alina Jade Barnett, Chaofan Chen |
| 2021 | CVPR | ECKPN: Explicit Class Knowledge Propagation Network for Transductive Few-Shot Learning. | Chaofan Chen, Xiaoshan Yang, Changsheng Xu, Xuhui Huang, Zhe Ma |
| 2020 | ICPR | A General Model for Learning Node and Graph Representations Jointly. | Chaofan Chen |
| 2020 | TrustCom | Hypergraph Attention Networks. | Chaofan Chen, Zelei Cheng, Zuotian Li, Manyi Wang |
| 2019 | HCOMP | Interpretable Image Recognition with Hierarchical Prototypes. | Peter Hase, Chaofan Chen, Oscar Li, Cynthia Rudin |
| 2018 | AAAI | Deep Learning for Case-Based Reasoning Through Prototypes: A Neural Network That Explains Its Predictions. | Oscar Li, Hao Liu, Chaofan Chen, Cynthia Rudin |
| 2018 | AISTATS | An Optimization Approach to Learning Falling Rule Lists. | Chaofan Chen, Cynthia Rudin |