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ORCIDChaofan Chen
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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2020 – today
- 2024
[j16]Wen Sun, Chaofan Chen, Jin-Kao Hao
, Wenlong Li, Qinghua Wu, Yuning Chen:
A knowledge-based iterated local search for the weighted total domination problem. Inf. Sci. 665: 120364 (2024)- [c22]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 - [c21]Chaofan Chen, Wenhao Zhong, Kezhong Lu:
Semi-supervised Online Elastic Stochastic Configuration Network to Deal with Concept Drift and Class Imbalance in Data Streams. IJCNN 2024: 1-8 - [i14]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) - 2023
- [j15]Chaofan Chen, Xiaoshan Yang, Jinpeng Zhang, Bo Dong, Changsheng Xu:
Category Knowledge-Guided Parameter Calibration for Few-Shot Object Detection. IEEE Trans. Image Process. 32: 1092-1107 (2023) - [c20]Yuyang Wanyan, Xiaoshan Yang, Chaofan Chen, Changsheng Xu:
Active Exploration of Multimodal Complementarity for Few-Shot Action Recognition. CVPR 2023: 6492-6502 - [c19]Han Jiang, Xiaoshan Yang, Chaofan Chen, Changsheng Xu:
Fine-grained Primitive Representation Learning for Compositional Zero-shot Classification. ICME 2023: 456-461 - [c18]Yanchen Jessie Ou, Alina Jade Barnett, Anika Mitra, Fides Regina Schwartz, Chaofan Chen, Lars J. Grimm, Joseph Y. Lo, Cynthia Rudin:
A user interface to communicate interpretable AI decisions to radiologists. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2023 - [c17]Yanchen Ou, Alina Jade Barnett, Anika Mitra, Fides Regina Schwartz, Chaofan Chen, Lars J. Grimm, Joseph Y. Lo, Cynthia Rudin:
A user interface to communicate interpretable AI decisions to radiologists (Erratum). Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2023 - [c16]Chiyu Ma, Brandon Zhao, Chaofan Chen, Cynthia Rudin:
This Looks Like Those: Illuminating Prototypical Concepts Using Multiple Visualizations. NeurIPS 2023 - [i13]Chiyu Ma, Brandon Zhao, Chaofan Chen, Cynthia Rudin:
This Looks Like Those: Illuminating Prototypical Concepts Using Multiple Visualizations. CoRR abs/2310.18589 (2023) - 2022
- [j14]Melissa Kimble, Steven Allers, K. Campbell, Chaofan Chen, Laura M. Jackson, Benjamin L. King, Samantha Silverbrand, G. York, Kate Beard:
medna-metadata: an open-source data management system for tracking environmental DNA samples and metadata. Bioinform. 38(19): 4589-4597 (2022) - [j13]Chaofan Chen, Kangcheng Lin, Cynthia Rudin, Yaron Shaposhnik, Sijia Wang, Tong Wang:
A holistic approach to interpretability in financial lending: Models, visualizations, and summary-explanations. Decis. Support Syst. 152: 113647 (2022) - [c15]Jon Donnelly, Alina Jade Barnett, Chaofan Chen:
Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes. CVPR 2022: 10255-10265 - [c14]Sisi Liu, Chaofan Chen, Yuan Sun:
Paragraph-level Tibetan Question Generation for Machine Reading Comprehension. IALP 2022: 280-285 - [c13]Alina Jade Barnett, Vaibhav Sharma, Neel Gajjar, Jerry Fang, Fides Regina Schwartz, Chaofan Chen, Joseph Y. Lo, Cynthia Rudin:
Interpretable deep learning models for better clinician-AI communication in clinical mammography. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2022 - [c12]Chaofan Chen, Xiaoshan Yang, Ming Yan, Changsheng Xu:
Attribute-guided Dynamic Routing Graph Network for Transductive Few-shot Learning. ACM Multimedia 2022: 6259-6268 - [c11]Chaofan Chen, Wendi Nie, Yaoxin Duan, Victor C. S. Lee, Kai Liu, Huamin Li:
An Adaptive Data Rate-Based Task Offloading Scheme in Vehicular Networks. MSN 2022: 877-884 - [i12]Qinyu Hu, Songyang Wu, Wenqi Sun, Zhushou Tang, Chaofan Chen, Zhiguo Ding, Xiaomei Zhang:
Measurement of the Usage of Web Clips in Underground Economy. CoRR abs/2209.03319 (2022) - 2021
- [j12]Changhong Wang, Zhongshan Zhang, Jiayi Wu, Chaofan Chen, Fei Gao:
An overview of protected satellite communications in intelligent age. Sci. China Inf. Sci. 64(6) (2021) - [j11]Chaofan Chen, Xiangming Li, Xia-qing Miao, Xiangyuan Bu, Shuai Wang:
Low-Complexity Polar Coded Noncoherent Detection Using Information Reconstruction. IEEE Commun. Lett. 25(8): 2492-2496 (2021) - [j10]Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin:
A case-based interpretable deep learning model for classification of mass lesions in digital mammography. Nat. Mach. Intell. 3(12): 1061-1070 (2021) - [j9]Yuan Sun, Andong Chen, Chaofan Chen, Tianci Xia, Xiaobing Zhao:
A Joint Model for Representation Learning of Tibetan Knowledge Graph Based on Encyclopedia. ACM Trans. Asian Low Resour. Lang. Inf. Process. 20(2): 27:1-27:17 (2021) - [j8]Chaofan Chen, Shengsheng Qian, Quan Fang, Changsheng Xu:
HAPGN: Hierarchical Attentive Pooling Graph Network for Point Cloud Segmentation. IEEE Trans. Multim. 23: 2335-2346 (2021) - [c10]Chaofan Chen, Xiaoshan Yang, Changsheng Xu, Xuhui Huang, Zhe Ma:
ECKPN: Explicit Class Knowledge Propagation Network for Transductive Few-Shot Learning. CVPR 2021: 6596-6605 - [i11]Cynthia Rudin, Chaofan Chen, Zhi Chen, Haiyang Huang, Lesia Semenova, Chudi Zhong:
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges. CoRR abs/2103.11251 (2021) - [i10]Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin:
IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography. CoRR abs/2103.12308 (2021) - [i9]Chaofan Chen, Kangcheng Lin, Cynthia Rudin, Yaron Shaposhnik, Sijia Wang, Tong Wang:
A Holistic Approach to Interpretability in Financial Lending: Models, Visualizations, and Summary-Explanations. CoRR abs/2106.02605 (2021) - [i8]Chaofan Chen, Xiaoshan Yang, Changsheng Xu, Xuhui Huang, Zhe Ma:
ECKPN: Explicit Class Knowledge Propagation Network for Transductive Few-shot Learning. CoRR abs/2106.08523 (2021) - [i7]Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao, Chaofan Chen, Yinhao Ren, Joseph Y. Lo, Cynthia Rudin:
Interpretable Mammographic Image Classification using Cased-Based Reasoning and Deep Learning. CoRR abs/2107.05605 (2021) - [i6]Jon Donnelly, Alina Jade Barnett, Chaofan Chen:
Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes. CoRR abs/2111.15000 (2021) - 2020
- [b1]Chaofan Chen:
Interpretability by Design: New Interpretable Machine Learning Models and Methods. Duke University, Durham, NC, USA, 2020 - [j7]Chaofan Chen, Shuai Wang, Li Li, Sheng Ke, Changhong Wang, Xiangyuan Bu:
Intelligent Covert Satellite Communication for Military Robot Swarm. IEEE Access 8: 5363-5382 (2020) - [j6]Jiawei Li, Jing Jiang, Weihua Wu, Chaofan Chen:
Consensus Continuous-Discrete Gaussian Filtering Using Fully Symmetric Interpolatory Quadrature. IEEE Access 8: 66353-66364 (2020) - [j5]Ye Zhu, Chaofan Chen, Gang Yan, Yingchun Guo, Yongfeng Dong:
AR-Net: Adaptive Attention and Residual Refinement Network for Copy-Move Forgery Detection. IEEE Trans. Ind. Informatics 16(10): 6714-6723 (2020) - [c9]Chaofan Chen:
A General Model for Learning Node and Graph Representations Jointly. ICPR 2020: 2867-2873 - [c8]Chaofan Chen, Zelei Cheng, Zuotian Li, Manyi Wang:
Hypergraph Attention Networks. TrustCom 2020: 1560-1565
2010 – 2019
- 2019
- [j4]Chaofan Chen, Li Li, Li Wang, Shuai Wang, Xiangming Li, George K. Karagiannidis:
Noncoherent Detection With Polar Codes. IEEE Access 7: 6362-6372 (2019) - [j3]Yuan Sun, Chaofan Chen, Tianci Xia, Xiaobing Zhao:
QuGAN: Quasi Generative Adversarial Network for Tibetan Question Answering Corpus Generation. IEEE Access 7: 116247-116255 (2019) - [j2]Yuan Sun, Like Wang, Chaofan Chen, Tianci Xia, Xiaobing Zhao:
Improved Distant Supervised Model in Tibetan Relation Extraction Using ELMo and Attention. IEEE Access 7: 173054-173062 (2019) - [j1]Changhong Wang, Siyang Sun, Xiangyuan Bu, Chaofan Chen, Fei Gao:
Filtering wideband slot antenna using split-ring resonator. IEICE Electron. Express 16(23): 20190647 (2019) - [c7]Peter Hase, Chaofan Chen, Oscar Li, Cynthia Rudin:
Interpretable Image Recognition with Hierarchical Prototypes. HCOMP 2019: 32-40 - [c6]Minnan Liu, Chaofan Chen, Yongfeng Ma:
A Low Latency Hardware Implementation Architecture for Polar Code. ICCT 2019: 1443-1448 - [c5]Chaofan Chen, Oscar Li, Daniel Tao, Alina Barnett, Cynthia Rudin, Jonathan Su:
This Looks Like That: Deep Learning for Interpretable Image Recognition. NeurIPS 2019: 8928-8939 - [i5]Peter Hase, Chaofan Chen, Oscar Li, Cynthia Rudin:
Interpretable Image Recognition with Hierarchical Prototypes. CoRR abs/1906.10651 (2019) - 2018
- [c4]Oscar Li, Hao Liu, Chaofan Chen, Cynthia Rudin:
Deep Learning for Case-Based Reasoning Through Prototypes: A Neural Network That Explains Its Predictions. AAAI 2018: 3530-3537 - [c3]Chaofan Chen, Cynthia Rudin:
An Optimization Approach to Learning Falling Rule Lists. AISTATS 2018: 604-612 - [i4]Chaofan Chen, Oscar Li, Alina Barnett, Jonathan Su, Cynthia Rudin:
This looks like that: deep learning for interpretable image recognition. CoRR abs/1806.10574 (2018) - [i3]Chaofan Chen, Kangcheng Lin, Cynthia Rudin, Yaron Shaposhnik, Sijia Wang, Tong Wang:
An Interpretable Model with Globally Consistent Explanations for Credit Risk. CoRR abs/1811.12615 (2018) - 2017
- [c2]Yali Luo, Xiulai Li, Chaofan Chen, Mingrui Chen:
An Improved Algorithm Based on LSB. PAAP 2017: 386-392 - [c1]Xiulai Li, Chaofan Chen, Yali Luo, Mingrui Chen:
Optimization Scheme Based on Parallel Computing Technology. PAAP 2017: 504-513 - [i2]Chaofan Chen, Cynthia Rudin:
An optimization approach to learning falling rule lists. CoRR abs/1710.02572 (2017) - [i1]Oscar Li, Hao Liu, Chaofan Chen, Cynthia Rudin:
Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains its Predictions. CoRR abs/1710.04806 (2017)
Coauthor Index
aka: Alina Jade Barnett
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