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Tensorflow
README.md

README.md

UnsupervisedLearning-WGAN

Introduction

This directory contains benchmarks based on Wasserstein GANs, a refinement to the original generative adversarial network.

GAN is an unsupervised learning model that uses two networks - a generator and a discriminator. As training progresses, the generator attempts to produce increasingly convincing data, while the discriminator attempts to distinguish between data produced by the generator and data from the original dataset.

References

Below are some useful resources on WGANs and GANs in general.