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Transferability of features for neural networks links to adversarial attacks and defences
The reason for the existence of adversarial samples is still barely understood. Here, we explore the transferability of learned features to Out-of-Distribution (OoD) classes. We do this by assessing neural networks’ capability to encode the existing features, revealing an intriguing connection with...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9045664/ https://www.ncbi.nlm.nih.gov/pubmed/35476838 http://dx.doi.org/10.1371/journal.pone.0266060 |