data-efficient-gans
GAN trainer
Improves GAN training efficiency by incorporating data augmentation
[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
1k stars
18 watching
175 forks
Language: Python
last commit: almost 2 years agodata-efficientgansgenerative-adversarial-networkimage-generationneurips-2020pytorchtensorflow
Related projects:
| Repository | Description | Stars |
|---|---|---|
 justinpinkney/data-efficient-gans | An implementation of Differentiable Augmentation for GAN training to improve data efficiency. | 11 |
 tensorflow/gan | Provides tools and utilities for training and evaluating Generative Adversarial Networks (GANs) in TensorFlow | 944 |
 subeeshvasu/awsome-gan-training | A curated collection of resources and techniques for training Generative Adversarial Networks (GANs) with various architectures, normalization methods, and regularization strategies. | 27 |
 dmitryulyanov/age | This repository provides code for training Generative Adversarial Networks (GANs) for various image datasets, including face generation. | 285 |
 stormraiser/gan-weight-norm | Improves the performance of Generative Adversarial Networks by normalizing weights and batch data | 181 |
 akanimax/pro_gan_pytorch | Implementation of a deep learning model for generating high-quality images with improved stability and variation. | 538 |
 hanzhanggit/stackgan-v2 | Software framework for training and evaluating generative models of images and text based on adversarial networks | 847 |
 ahmedfgad/neuralgenetic | Trains artificial neural networks using the genetic algorithm | 241 |
 caogang/wgan-gp | 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 |
| ahmedfgad/cnngenetic | Trains CNNs using a genetic algorithm for classification problems where one class per sample is allowed. | 22 |
 zcemycl/matlab-gan | A collection of MATLAB implementations for Generative Adversarial Networks (GANs) and related deep learning techniques | 190 |
 csailvision/gandissect | Visualizes and understands internal representations of generative adversarial networks (GANs) to analyze their behavior and improve performance. | 1,770 |
 ntedgi/node-efficientnet | A Node.js implementation of the EfficientNet deep learning model architecture. | 258 |
 mailmahee/pytorch-generative-adversarial-networks | An implementation of Generative Adversarial Networks in PyTorch for generating realistic data from a given distribution. | 32 |
 eth-sri/diffai | Trains neural networks to be provably robust against adversarial examples using abstract interpretation techniques. | 219 |