readme

labml_nn/gan/__init__.py

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+"""
+---
+title: Generative Adversarial Networks
+summary: >
+ A set of PyTorch implementations/tutorials of GANs.
+---
+
+# Generative Adversarial Networks
+
+* [Original GAN](original/index.html)
+* [GAN with deep convolutional network](dcgan/index.html)
+* [Cycle GAN](cycle_gan/index.html)
+* [Wasserstein GAN](wasserstein/index.html)
+"""

labml_nn/gan/cycle_gan/readme.md

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+# [Cycle GAN](https://nn.labml.ai/gan/cycle_gan/index.html)
+
+This is a [PyTorch](https://pytorch.org) implementation/tutorial of the paper
+[Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks](https://arxiv.org/abs/1703.10593).

labml_nn/gan/dcgan/readme.md

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+# [Deep Convolutional Generative Adversarial Networks - DCGAN](https://nn.labml.ai/gan/dcgan/index.html)
+
+This is a [PyTorch](https://pytorch.org) implementation of paper
+[Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks](https://arxiv.org/abs/1511.06434).

labml_nn/gan/original/readme.md

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+# [Generative Adversarial Networks - GAN](https://nn.labml.ai/gan/original/index.html)
+
+This is an annotated implementation of
+[Generative Adversarial Networks](https://arxiv.org/abs/1406.2661).

labml_nn/gan/wasserstein/__init__.py

@@ -4,6 +4,8 @@ title: Wasserstein GAN (WGAN)
 summary: A simple PyTorch implementation/tutorial of Wasserstein Generative Adversarial Networks (WGAN) loss functions.
 ---
 
+# Wasserstein GAN (WGAN)
+
 This is an implementation of
 [Wasserstein GAN](https://arxiv.org/abs/1701.07875).
 

labml_nn/gan/wasserstein/readme.md

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+# [Wasserstein GAN - WGAN](https://nn.labml.ai/gan/wasserstein/index.html)
+
+This is an implementation of
+[Wasserstein GAN](https://arxiv.org/abs/1701.07875).