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

Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai

Awesome Generative Adversarial Networks with tensorflow

Simple Implementation of many GAN models with PyTorch.

Reimplementation of GANs

Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.

Code for training and evaluation of the model from "Language Generation with Recurrent Generative Adversarial Networks without Pre-training"

Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN

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

A minimal implementaion (less than 150 lines of code with visualization) of DCGAN/WGAN in PyTorch with jupyter notebooks

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

Resources and Implementations of Generative Adversarial Nets which are focusing on how to stabilize training process and generate high quality images: DCGAN, WGAN, EBGAN, BEGAN, etc.

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.

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

Tensorflow implementation of different GANs and their comparisions

Thesis project done on Generation Financial Time-Series with GANs. The project was a collaboration between Wholesale Banking Advanced Analytics team with ING and University Maastricht.

implementation of several GANs with pytorch

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