Machine learning, in numpy

Collection of generative models in Tensorflow

Collection of generative models in Pytorch version.

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

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

Awesome Generative Adversarial Networks with tensorflow

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

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

Improved WGAN in Pytorch

Reimplementation of GANs

Chainer implementation of recent GAN variants

Simple Implementation of many GAN models with PyTorch.

Pytorch implementation of Wasserstein GANs with Gradient Penalty

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

PyTorch implementation of DCGAN, WGAN-GP and SNGAN.

DCGAN LSGAN WGAN-GP DRAGAN PyTorch

GAN and VAE implementations to generate artificial EEG data to improve motor imagery classification. Data based on BCI Competition IV, datasets 2a. Final project for UCLA's EE C247: Neural Networks and Deep Learning course.

implementation of several GANs with pytorch

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

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