Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Keras Gan | 8,842 | a year ago | 142 | mit | Python | |||||
Keras implementations of Generative Adversarial Networks. | ||||||||||
Gans | 776 | 2 years ago | 18 | mit | Jupyter Notebook | |||||
Generative Adversarial Networks implemented in PyTorch and Tensorflow | ||||||||||
Adversarial Examples Pytorch | 353 | a year ago | 4 | Python | ||||||
Implementation of Papers on Adversarial Examples | ||||||||||
Pytorch Mnist Celeba Gan Dcgan | 302 | 5 years ago | 9 | Python | ||||||
Pytorch implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Networks (DCGAN) for MNIST and CelebA datasets | ||||||||||
Pytorch Mnist Celeba Cgan Cdcgan | 221 | 7 years ago | 6 | Python | ||||||
Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset | ||||||||||
Generative_adversarial_networks_101 | 190 | 5 months ago | mit | Jupyter Notebook | ||||||
Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets. | ||||||||||
Adversarialvariationalbayes | 185 | 6 years ago | 3 | mit | Jupyter Notebook | |||||
This repository contains the code to reproduce the core results from the paper "Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks". | ||||||||||
Tensorflow Infogan | 148 | 7 years ago | 5 | Python | ||||||
:dolls: InfoGAN: Interpretable Representation Learning | ||||||||||
Generate_to_adapt | 115 | 5 years ago | 3 | Python | ||||||
Implementation of "Generate To Adapt: Aligning Domains using Generative Adversarial Networks" | ||||||||||
Capsule Gan | 111 | 4 years ago | 2 | mit | Jupyter Notebook | |||||
Code for my Master thesis on "Capsule Architecture as a Discriminator in Generative Adversarial Networks". |