/Generative_Adversarial_Networks

Implements a GAN in PyTorch

Primary LanguageJupyter Notebook

Generative_Adversarial_Networks

Generative adversarial networks (GANs) are a class of artificial intelligence algorithms used in unsupervised machine learning, implemented by a system of two neural networks contesting with each other in a zero-sum game framework. They were introduced by Ian Goodfellow in 2014.

The branch plain_pytorch_implementation contains the PyTorch implementation of the same.

Results :

  • Before start of training :

Before start of training

  • After one iteration :

After one iteration

  • After two iterations :

After two iteration

  • After some hundred thousands iterations :

After some hundred thousands iterations

Generator's Loss : gen-loss

Discriminator's Loss : disc-loss

Well here are some results from the Deep Convolutional GAN on CIFAR-10 dataset

GIF of epochs