
gan · GitHub Topics · GitHub
Dec 15, 2025 · gan Generative adversarial networks (GAN) are a class of generative machine learning frameworks. A GAN consists of two competing neural networks, often termed the …
GitHub - tensorflow/gan: Tooling for GANs in TensorFlow
TF-GAN is a lightweight library for training and evaluating Generative Adversarial Networks (GANs). Can be installed with pip using pip install tensorflow-gan, and used with import …
The GAN is dead; long live the GAN! A Modern Baseline GAN …
Code for NeurIPS 2024 paper - The GAN is dead; long live the GAN! A Modern Baseline GAN - by Huang et al. - brownvc/R3GAN
GitHub - eriklindernoren/PyTorch-GAN: PyTorch implementations …
Softmax GAN is a novel variant of Generative Adversarial Network (GAN). The key idea of Softmax GAN is to replace the classification loss in the original GAN with a softmax cross …
GitHub - Yangyangii/GAN-Tutorial: Simple Implementation of …
Simple Implementation of many GAN models with PyTorch. - Yangyangii/GAN-Tutorial
GitHub - tkarras/progressive_growing_of_gans: Progressive …
The Progressive GAN code repository contains a command-line tool for recreating bit-exact replicas of the datasets that we used in the paper. The tool also provides various utilities for …
PyTorch Pretrained GANs - GitHub
Apr 11, 2021 · Each type of GAN is contained in its own folder and has a make_GAN_TYPE function. For example, make_bigbigan creates a BigBiGAN with the format of the …
GitHub - mingjie0508/MAE_GAN: Masked Autoencoder (MAE) for …
MAE_GAN In this project, we explore the use of Masked Autoencoder (MAE) in inpainting tasks. By combining MAE with GAN and using perceptual loss functions, we can obtain clear, …
GitHub - gordicaleksa/pytorch-GANs: My implementation of …
This repo contains PyTorch implementation of various GAN architectures. It's aimed at making it easy for beginners to start playing and learning about GANs. All of the repos I found do …
GitHub - yfeng95/GAN: Resources and Implementations of …
GAN before using JS divergence has the problem of non-overlapping, leading to mode collapse and convergence difficulty. Use EM distance or Wasserstein-1 distance, so GAN solve the two …