adagan
GAN training mixer
An implementation of an algorithm to train mixtures of Generative Adversarial Networks (GANs) for generative modeling tasks
AdaGAN: greedy iterative procedure to train mixtures of GANs
76 stars
4 watching
18 forks
Language: Python
last commit: about 7 years ago
Linked from 1 awesome list
Related projects:
Repository | Description | Stars |
---|---|---|
| An implementation of an improved training algorithm for generative adversarial networks (GANs), specifically designed to stabilize the training process using a gradient penalty term. | 1,515 |
| Improves GAN training efficiency by incorporating data augmentation | 1,286 |
| A curated collection of resources and techniques for training Generative Adversarial Networks (GANs) with various architectures, normalization methods, and regularization strategies. | 27 |
| A deep learning implementation of a generative adversarial network for generating images from text descriptions. | 340 |
| A collection of Torch implementations for training various types of Generative Adversarial Networks (GANs) | 55 |
| This repository provides code for training Generative Adversarial Networks (GANs) for various image datasets, including face generation. | 285 |
| Trains artificial neural networks using the genetic algorithm | 241 |
| Software framework for training and evaluating generative models of images and text based on adversarial networks | 847 |
| Improves the performance of Generative Adversarial Networks by normalizing weights and batch data | 181 |
| Provides tools and utilities for training and evaluating Generative Adversarial Networks (GANs) in TensorFlow | 944 |
| A framework for unpaired cross-domain image translation using GANs with adaptive normalization parameters and weight-sharing. | 718 |
| An implementation of Differentiable Augmentation for GAN training to improve data efficiency. | 11 |
| Trains CNNs using a genetic algorithm for classification problems where one class per sample is allowed. | 22 |
| An implementation of Generative Adversarial Networks in PyTorch for generating realistic data from a given distribution. | 32 |
| A PyTorch implementation of a Generative Adversarial Network (GAN) for discovering cross-domain relations. | 1,084 |