Bibliography (11):

1. https://github.com/MadryLab/cifar10_challenge

2. Explaining and Harnessing Adversarial Examples

3. Smooth Adversarial Training

4. ​ ‘MLP NN’ directory

5. Deep Residual Learning for Image Recognition

6. Wikipedia Bibliography:

   1. MNIST database

   2. https://en.wikipedia.org/wiki/Adversarial_machine_learning#Adversarial_examples  :

      https://en.wikipedia.org/wiki/Adversarial_machine_learning#Adversarial_examples

   3. https://en.wikipedia.org/wiki/Proximal_gradient_methods_for_learning  :

      https://en.wikipedia.org/wiki/Proximal_gradient_methods_for_learning

   4. Cross-entropy

   5. https://en.wikipedia.org/wiki/Saddle_point  :

      https://en.wikipedia.org/wiki/Saddle_point

   6. Data augmentation