Generative models with tensorflow version 2.0 style

• Final update: 2019. 12. 1.
• All right reserved @ Il Gu Yi, Soochul Park

This repository is a collection of various generative models (GAN, VAE, Normalizing flow, Autoregressive models, etc) implemented by TensorFlow version 2.0 style

Getting Started

Prerequisites

• TensorFlow 2.0
• Python 3.6
• Python libraries:
  • numpy, matplotlib, PIL, imageio
  • urllib, zipfile
• TensorFlow libraries & extensions:
  • tensorflow_probability
• Jupyter notebook
• OS X and Linux (Not validated on Windows OS)

Contents

Generative Adversarial Networks (GANs) [with MNIST and Fashion MNIST]

DCGAN (Deep Convolutional GAN)

• Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks paper arXiv:1511.06434
• dcgan.ipynb

MNIST	Fashion MNIST

Conditional GAN

• Conditional Generative Adversarial Nets arXiv:1411.1784
• cgan.ipynb

MNIST
Fashion MNIST

LSGAN

• Least Squares Generative Adversarial Networks arXiv:1611.04076
• lsgan.ipynb

MNIST	Fashion MNIST

BiGAN

• Adversarial Feature Learning arXiv:1605.09782
• bigan.ipynb

MNIST
Fashion MNIST

Wasserstein GAN

• Wasserstein GAN arXiv:1701.07875
• wgan.ipynb

MNIST	Fashion MNIST

WGAN-GP

• Improved Training of Wasserstein GANs arXiv:1704.00028
• wgan-gp.ipynb

MNIST	Fashion MNIST

Pix2Pix (Image Translation)

• Image-to-Image Translation with Conditional Adversarial Networks arXiv:1611.07004
• pix2pix.ipynb

facades
cityspaces

CycleGAN (Unpaired Image Translation)

• Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks arXiv:1703.10593
• cyclegan.ipynb

Latent Variable Models [with MNIST]

AutoEncoder (actually not generative model)

• autoencoder.ipynb

MNIST
Fashion MNIST

Denosing AutoEncoder

• dae.ipynb

AutoRegressive Models [with MNIST]

Fully Visible Sigmoid Belief Networks

• fvsbn.ipynb

MNIST	Fashion MNIST

Neural Autoregressive Density Estimation

• Neural Autoregressive Distribution Estimation arXiv:1605.02226
• nade.ipynb

MNIST	Fashion MNIST

Transformer with MNIST

• Attention is All You Need arXiv:1706.03762
• transformer_mnist.ipynb

MNIST

LSTM with MNIST

• lstm_mnist.ipynb

MNIST

Normalizing Flow Models [with MNIST]

NICE: Non-Linear Independent Components Estimation

• nice.ipynb

Author

Il Gu Yi, Soochul Park

Slides

Notion link