Vanilla GAN trained to generate adversarial examples for MNIST dataset.
Python source file has been provided for GAN implementation:
- Implementation using TensorFlow.
- Different possible Loss functions provided.
- Trained on MNIST dataset.
MINIMAX formulation of GANs:
Adversarial example generated during the training process, showing the least mode collapse and more variance in the number of digits produced by the generator:
