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Nhan đề : 
RELAX: Representation Learning Explainability
Tác giả : 
Kristoffer K., Wickstrøm
Daniel J., Trosten
Sigurd, Løkse
Năm xuất bản : 
2023
Nhà xuất bản : 
Springer
Tóm tắt : 
Despite the significant improvements that self-supervised representation learning has led to when learning from unlabeled data, no methods have been developed that explain what influences the learned representation. We address this need through our proposed approach, RELAX, which is the first approach for attribution-based explanations of representations. Our approach can also model the uncertainty in its explanations, which is essential to produce trustworthy explanations. RELAX explains representations by measuring similarities in the representation space between an input and masked out versions of itself, providing intuitive explanations that significantly outperform the gradient-based baselines.
Mô tả: 
CC BY
URI: 
https://link.springer.com/article/10.1007/s11263-023-01773-2
https://dlib.phenikaa-uni.edu.vn/handle/PNK/8254
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