InfoGAN inspired neural network trained on zap50k images (using Tensorflow + tf-slim). Intermediate layers of the discriminator network are used to do image similarity.
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Updated
Jan 6, 2017 - Python
InfoGAN inspired neural network trained on zap50k images (using Tensorflow + tf-slim). Intermediate layers of the discriminator network are used to do image similarity.
🎎 InfoGAN: Interpretable Representation Learning
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 variations of GANs like conditional and Wasserstein.
Keras implementation of InfoGAN (work in progress)
GAN / DCGAN / InfoGAN / BEGAN ...
Resources and Implementations of Generative Adversarial Nets: GAN, DCGAN, WGAN, CGAN, InfoGAN
GANs Implementations in Keras
This is a deep learning code written in PyTorch that convert a given text into image.
Implement multiple gan including vanilla_gan, dcgan, cgan, infogan and wgan with tensorflow and dataset including mnist.
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
objected oriented implementation of InfoGAN using PyTorch
Semi-supervised InfoGAN
The basic tutorial of tensorflow
implement infoGAN using pytorch
Playing with MNIST. Machine Learning. Generative Models.
Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
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