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Generative Adversarial Networks with TensorFlow2, Keras and Python (Jupyter Notebooks Implementations)

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TF2-Keras-GAN-Notebooks

Generative Adversarial Networks (GANs) implemented using TF2/Keras in Juypter Notebooks with Colab Links.

Topics

  • Variational AutoEncoder
  • Simple GAN
  • DCGAN for Fashion MNIST
  • DCGAN for Anime Faces
  • DCGAN for Celebrity Faces
  • Pix2Pix for Maps
  • Pix2Pix for BnW-to-Color
  • Cycle-GAN for Apples-to-Oranges
  • Cycle-GAN for Horses-to-Zebras
  • Context Encoder
  • Disco-GAN Male vs Female
  • Super Resolution or SR-GAN
  • Mode Collapse Example
  • Convergence Failure Example
  • Conditional GAN (CGAN)
  • Semi Supervised GAN (SGAN)
  • InfoGAN
  • Auxiliary Classifier GAN
  • Pixel CNN
  • Wasserstein GAN (WGAN)
  • Least Squares GAN (LSGAN)
  • Improved WGAN (WGAN-GP)

Implementation and Results

Variational-AutoEncoder

Notebook

Simple-GAN

Notebook

DCGAN-Fashion-MNIST

Notebook

DCGAN-Anime-Faces

Notebook

DCGAN-Celebrity-Faces

Notebook

pix2pix-BnW-to-Color

Notebook

pix2pix-Maps

Notebook

cycle-gan-Apples-to-Oranges

Notebook

cycle-gan-Horses-to-Zebras

Notebook

context-encoder

Notebook

disco-gan-male-to-female

Notebook

super-resolution-srgan

Notebook

Mode-Collapse-Failure-in-GANs

Notebook

Convergence-Failure-in-GANs

Notebook

CGAN

Notebook

Semi-Supervised-GAN-or-SGAN

Notebook

InfoGAN

Notebook

Auxiliary-Classifier-GAN-or-ACGAN

Notebook

Pixel-CNN

Notebook

Wasserstein-GAN-or-WGAN

Notebook

Least-Squares-GAN-or-LSGAN

Notebook

Improved-WGAN-or-WGAN-GP

Notebook