【論文回顧】Towards Evaluating the Robustness of Neural Networks

時間 2021-01-02

標籤深度學習简体版

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paper notes: 1.this paper introduced three new attacks for L-0 L-2 L-infin distance metrics by defining different choices of objective function. Specifically, they are all based on the L-2 attack. 2.t

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1. [paper]Towards Evaluating the Robustness of Neural Networks(C&W)
2. Towards Evaluating the Robustness of Neural Networks論文解讀集合
3. The Unreasonable Effectiveness of Recurrent Neural Networks
4. 課程回顧-Convolutional Neural Networks
5. 論文《On the Number of Linear Regions of Deep Neural Networks》翻譯
6. Towards Deeper Graph Neural Networks
7. MUNN：Mutation Analysis of neural networks論文閱讀
8. On the Number of Linear Regions of Deep Neural Networks
9. 【論文回顧】The Limitations of Deep Learning in Adversarial Settings
10. Applications of Graph Neural Networks
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1. [paper]Towards Evaluating the Robustness of Neural Networks(C&W)
2. Towards Evaluating the Robustness of Neural Networks論文解讀集合
3. The Unreasonable Effectiveness of Recurrent Neural Networks
4. 課程回顧-Convolutional Neural Networks
5. 論文《On the Number of Linear Regions of Deep Neural Networks》翻譯
6. Towards Deeper Graph Neural Networks
7. MUNN：Mutation Analysis of neural networks論文閱讀
8. On the Number of Linear Regions of Deep Neural Networks
9. 【論文回顧】The Limitations of Deep Learning in Adversarial Settings
10. Applications of Graph Neural Networks

>>更多相關文章<<