A Framework for Learning Ante-hoc Explainable Models via Concepts-Reference-Cited by-同舟云学术

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A Framework for Learning Ante-hoc Explainable Models via Concepts

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Author:

Sarkar Anirban¹,Vijaykeerthy Deepak²,Sarkar Anindya¹,Balasubramanian Vineeth N¹

Affiliation:

1. IIT Hyderabad,Telangana,India

2. IBM Research,Bangalore,India

Funder

MoE

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9878378/9878366/09879843.pdf?arnumber=9879843

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. What Does a Model Really Look at?: Extracting Model-Oriented Concepts for Explaining Deep Neural Networks;IEEE Transactions on Pattern Analysis and Machine Intelligence;2024-07

2. A survey of explainable knowledge tracing;Applied Intelligence;2024-04

3. The Importance of Interpretability in AI Systems and Its Implications for Deep Learning;Advances in Computational Intelligence and Robotics;2024-02-23

4. In-Training Explainability Frameworks: A Method to Make Black-Box Machine Learning Models More Explainable;2023 IEEE International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT);2023-10-26

5. Explainable Deep Learning Methods in Medical Image Classification: A Survey;ACM Computing Surveys;2023-10-21

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