Collection of generative models in Tensorflow
Resources and Implementations of Generative Adversarial Nets: GAN, DCGAN, WGAN, CGAN, InfoGAN
Collection of generative models in Pytorch version.
learn code with tensorflow
#计算机科学#Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
Simple Implementation of many GAN models with PyTorch.
#计算机科学#Vanilla GAN implemented on top of keras/tensorflow enabling rapid experimentation & research. Branches correspond to implementations of stable GAN variations (i.e. ACGan, InfoGAN) and other promising ...
🎎 InfoGAN: Interpretable Representation Learning
implement infoGAN using pytorch
InfoGAN inspired neural network trained on zap50k images (using Tensorflow + tf-slim). Intermediate layers of the discriminator network are used to do image similarity.
#计算机科学#Pytorch implementations of generative models: VQVAE2, AIR, DRAW, InfoGAN, DCGAN, SSVAE
Repository for implementation of generative models with Tensorflow 1.x
Generative models (GAN, VAE, Diffusion Models, Autoregressive Models) implemented with Pytorch, Pytorch_lightning and hydra.
ProGAN with Standard, WGAN, WGAN-GP, LSGAN, BEGAN, DRAGAN, Conditional GAN, InfoGAN, and Auxiliary Classifier GAN training methods
Simple implementation of Least Squares Generative Adversarial Networks
Performance comparison of ACGAN, BEGAN, CGAN, DRAGAN, EBGAN, GAN, infoGAN, LSGAN, VAE, WGAN, WGAN_GP on cifar-10
PyTorch implemented generative models for CelebA dataset: DCGAN, LSGAN, WGAN, WGANGP, InfoGAN, BEGAN, VAE, VAEGAN