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  Improving Native CNN Robustness with Filter Frequency Regularization

Lukasik, J., Gavrikov, P., Keuper, J., & Keuper, M. (2023). Improving Native CNN Robustness with Filter Frequency Regularization. Transactions on Machine Learning Research, 2023, 1-36. Retrieved from https://openreview.net/forum?id=2wecNCpZ7Y.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000F-241E-8 Version Permalink: https://hdl.handle.net/21.11116/0000-000F-241F-7
Genre: Journal Article
Latex : Improving Native {CNN} Robustness with Filter Frequency Regularization

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 Creators:
Lukasik, Jovita1, Author           
Gavrikov, Paul1, Author
Keuper, Janis1, Author
Keuper, Margret2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society, ou_1116547              

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Language(s): eng - English
 Dates: 2023
 Publication Status: Published online
 Pages: 36 p.
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 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: lukasik2023improving
URI: https://openreview.net/forum?id=2wecNCpZ7Y
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Title: Transactions on Machine Learning Research
Source Genre: Journal
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Publ. Info: New York, NY : TMLR
Pages: - Volume / Issue: 2023 Sequence Number: - Start / End Page: 1 - 36 Identifier: ISSN: 2835-8856