Python GS-WGAN Resources

Generative Adversarial Notebooks Collection of my Generative Adversarial Network implementations Most codes are for python3, most notebooks works on C

Recommendation Our GAN based work for facial attribute editing - AttGAN. News 8 April 2019: We re-implement these GANs by Tensorflow 2! The old versio

Chainer-GAN-lib This repository collects chainer implementation of state-of-the-art GAN algorithms. These codes are evaluated with the inception score

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

tensorflow-generative-model-collections Tensorflow implementation of various GANs and VAEs. Related Repositories Pytorch version Pytorch version of th

WGAN-GP An pytorch implementation of Paper "Improved Training of Wasserstein GANs". Prerequisites Python, NumPy, SciPy, Matplotlib A recent NVIDIA GPU

pytorch-generative-model-collections Original : [Tensorflow version] Pytorch implementation of various GANs. This repository was re-implemented with r

Overview PyTorch 0.4.1 | Python 3.6.5 Annotated implementations with comparative introductions for minimax, non-saturating, wasserstein, wasserstein g

GS-WGAN This repository contains the implementation for GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators (NeurIPS

numpy-ml Ever wish you had an inefficient but somewhat legible collection of machine learning algorithms implemented exclusively in NumPy? No? Install