RELAX: Representation Learning Explainability
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Springer
2023
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Online Access: | https://link.springer.com/article/10.1007/s11263-023-01773-2 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8254 |
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oai:localhost:PNK-82542023-04-25T02:00:35Z RELAX: Representation Learning Explainability Kristoffer K., Wickstrøm Daniel J., Trosten Sigurd, Løkse RELAX Learning Explainability CC BY 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. 2023-04-25T02:00:35Z 2023-04-25T02:00:35Z 2023 Book https://link.springer.com/article/10.1007/s11263-023-01773-2 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8254 en application/pdf Springer |
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Digital Phenikaa |
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Digital Phenikaa |
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English |
topic |
RELAX Learning Explainability |
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RELAX Learning Explainability Kristoffer K., Wickstrøm Daniel J., Trosten Sigurd, Løkse RELAX: Representation Learning Explainability |
description |
CC BY |
format |
Book |
author |
Kristoffer K., Wickstrøm Daniel J., Trosten Sigurd, Løkse |
author_facet |
Kristoffer K., Wickstrøm Daniel J., Trosten Sigurd, Løkse |
author_sort |
Kristoffer K., Wickstrøm |
title |
RELAX: Representation Learning Explainability |
title_short |
RELAX: Representation Learning Explainability |
title_full |
RELAX: Representation Learning Explainability |
title_fullStr |
RELAX: Representation Learning Explainability |
title_full_unstemmed |
RELAX: Representation Learning Explainability |
title_sort |
relax: representation learning explainability |
publisher |
Springer |
publishDate |
2023 |
url |
https://link.springer.com/article/10.1007/s11263-023-01773-2 https://dlib.phenikaa-uni.edu.vn/handle/PNK/8254 |
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1764177435395358720 |
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8.891145 |