Collection of generative models in Tensorflow
-
Updated
Aug 8, 2022 - Python
Collection of generative models in Tensorflow
Collection of generative models in Pytorch version.
Code for training and evaluation of the model from "Language Generation with Recurrent Generative Adversarial Networks without Pre-training"
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.
A Tensorflow implementation of GAN, WGAN and WGAN with gradient penalty.
Tensorflow implementation of different GANs and their comparisions
🚀 Variants of GANs most easily implemented as TensorFlow2. GAN, DCGAN, LSGAN, WGAN, WGAN-GP, DRAGAN, ETC...
DCGAN and WGAN implementation on Keras for Bird Generation
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.
ProGAN with Standard, WGAN, WGAN-GP, LSGAN, BEGAN, DRAGAN, Conditional GAN, InfoGAN, and Auxiliary Classifier GAN training methods
Add a description, image, and links to the wgan topic page so that developers can more easily learn about it.
To associate your repository with the wgan topic, visit your repo's landing page and select "manage topics."