Towards a theoretical understanding of the robustness of variational autoencoders
We make inroads into understanding the robustness of Variational Autoencoders (VAEs) to adversarial attacks and other input perturbations. While previous work has developed algorithmic approaches to attacking and defending VAEs, there remains a lack of formalization for what it means for a VAE to be...
| Main Authors: | , , , , |
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| 格式: | Conference item |
| 語言: | English |
| 出版: |
Journal of Machine Learning Research
2021
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