Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks

時間 2021-01-02

標籤 neural networks 简体版

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文章目錄概主要內容 Mustafa A., Khan S., Hayat M., Goecke R., Shen J., Shao L., Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks, arXiv preprint arXiv:1904.00887, 2019. 代碼概類似的, 是l

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1. [paper]Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
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4. On the Number of Linear Regions of Deep Neural Networks
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1. [paper]Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
2. [paper]ADVERSARIAL REPROGRAMMING OF NEURAL NETWORKS
3. Exploring the teaching of deep learning in neural networks
4. On the Number of Linear Regions of Deep Neural Networks
5. 關於Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks的理解
6. The Unreasonable Effectiveness of Recurrent Neural Networks
7. [paper]Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
8. Domain-Adversarial Training of Neural Networks
9. ICLR2014_Intriguing properties of neural networks
10. Xavier——Understanding the difficulty of training deep feedforward neural networks

>>更多相關文章<<