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[1] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[2] Micah Goldblum,et al. The Intrinsic Dimension of Images and Its Impact on Learning , 2021, ICLR.
[3] Fabio Roli,et al. Evasion Attacks against Machine Learning at Test Time , 2013, ECML/PKDD.
[4] Aleksander Madry,et al. Towards Deep Learning Models Resistant to Adversarial Attacks , 2017, ICLR.
[5] Aleksander Madry,et al. Adversarial Examples Are Not Bugs, They Are Features , 2019, NeurIPS.
[6] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[7] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[8] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[9] Naftali Tishby,et al. Opening the Black Box of Deep Neural Networks via Information , 2017, ArXiv.
[10] Hao Chen,et al. MagNet: A Two-Pronged Defense against Adversarial Examples , 2017, CCS.
[11] Joan Bruna,et al. Intriguing properties of neural networks , 2013, ICLR.
[12] H. Bourlard,et al. Auto-association by multilayer perceptrons and singular value decomposition , 1988, Biological Cybernetics.
[13] Natalia Gimelshein,et al. PyTorch: An Imperative Style, High-Performance Deep Learning Library , 2019, NeurIPS.
[14] Jonathon Shlens,et al. Explaining and Harnessing Adversarial Examples , 2014, ICLR.
[15] K. Jarrod Millman,et al. Array programming with NumPy , 2020, Nat..
[16] Bo Sun,et al. Adversarial Defense by Stratified Convolutional Sparse Coding , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[17] Wei Wang,et al. Generalized Autoencoder: A Neural Network Framework for Dimensionality Reduction , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops.