TF2-Keras-GAN-Notebooks
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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