Machine learning, in numpy

Collection of generative models in Tensorflow

Collection of generative models in Pytorch version.

wgan, wgan2(improved, gp), infogan, and dcgan implementation in lasagne, keras, pytorch

A pytorch implementation of Paper "Improved Training of Wasserstein GANs"

でぃーぷらーにんぐを無限にやってディープラーニングでDeepLearningするための実装CheatSheet

Awesome Generative Adversarial Networks with tensorflow

Implementations of (theoretical) generative adversarial networks and comparison without cherry-picking

[CVPR 2020 Workshop] A PyTorch GAN library that reproduces research results for popular GANs.

Chainer implementation of recent GAN variants

DCGAN LSGAN WGAN-GP DRAGAN Tensorflow 2

Improved WGAN in Pytorch

Simple Implementation of many GAN models with PyTorch.

Implementation of some different variants of GANs by tensorflow, Train the GAN in Google Cloud Colab, DCGAN, WGAN, WGAN-GP, LSGAN, SNGAN, RSGAN, RaSGAN, BEGAN, ACGAN, PGGAN, pix2pix, BigGAN

DCGAN LSGAN WGAN-GP DRAGAN PyTorch

Pytorch implementation of Wasserstein GANs with Gradient Penalty

A Tensorflow implementation of GAN, WGAN and WGAN with gradient penalty.

Keras implementation of "Image Inpainting via Generative Multi-column Convolutional Neural Networks" paper published at NIPS 2018

Repository for implementation of generative models with Tensorflow 1.x

A PyTorch implementation of SRGAN specific for Anime Super Resolution based on "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network". And another PyTorch WGAN-gp implementation of SRGAN referring to "Improved Training of Wasserstein GANs".

TensorFlow implementations of Wasserstein GAN with Gradient Penalty (WGAN-GP), Least Squares GAN (LSGAN), GANs with the hinge loss.

Pure tensorflow implementation of progressive growing of GANs

speech enhancement GAN on waveform/log-power-spectrum data using Improved WGAN

Tensorflow Implementation of Paper "Improved Training of Wasserstein GANs"

Performance comparison of ACGAN, BEGAN, CGAN, DRAGAN, EBGAN, GAN, infoGAN, LSGAN, VAE, WGAN, WGAN_GP on cifar-10

Improved Wasserstein GAN (WGAN-GP) application on medical (MRI) images

Simple Pytorch implementations of most used Generative Adversarial Network (GAN) varieties.

🚀 Variants of GANs most easily implemented as TensorFlow2. GAN, DCGAN, LSGAN, WGAN, WGAN-GP, DRAGAN, ETC...

Playing with MNIST. Machine Learning. Generative Models.

Keras model and tensorflow optimization of 'improved Training of Wasserstein GANs'