From GAN to WGAN
Par un écrivain mystérieux
Description
[Updated on 2018-09-30: thanks to Yoonju, we have this post translated in Korean!] [Updated on 2019-04-18: this post is also available on arXiv.]
Generative adversarial network (GAN) has shown great results in many generative tasks to replicate the real-world rich content such as images, human language, and music. It is inspired by game theory: two models, a generator and a critic, are competing with each other while making each other stronger at the same time.
![From GAN to WGAN](https://production-media.paperswithcode.com/methods/Screen_Shot_2020-05-25_at_3.01.45_PM.png)
WGAN GP Explained
![From GAN to WGAN](https://machinelearningmastery.com/wp-content/uploads/2019/05/Algorithm-for-the-Wasserstein-Generative-Adversarial-Networks-1.png)
How to Develop a Wasserstein Generative Adversarial Network (WGAN) From Scratch
![From GAN to WGAN](https://media.springernature.com/lw685/springer-static/image/chp%3A10.1007%2F978-3-031-22953-4_3/MediaObjects/522237_1_En_3_Fig4_HTML.png)
Comparing Beta-VAE to WGAN-GP for Time Series Augmentation to Improve Classification Performance
![From GAN to WGAN](https://i.stack.imgur.com/6u9fZ.png)
generative models - How to interprete Discriminator and Generator loss in WGAN - Cross Validated
![From GAN to WGAN](https://jacobjackson.com/img/kurach_fig2.png)
Gradients of GAN Objectives
![From GAN to WGAN](https://i.imgur.com/hRNF9FL.jpg)
Common Training Loss Curve of DCGAN and WGAN - CV Notes
![From GAN to WGAN](https://www.researchgate.net/publication/339998063/figure/fig1/AS:870278389317637@1584501945812/Wasserstein-GAN-WGAN.jpg)
Wasserstein GAN (WGAN). Download Scientific Diagram
![From GAN to WGAN](https://pub.mdpi-res.com/applsci/applsci-10-01449/article_deploy/html/images/applsci-10-01449-g001.png?1583505482)
Applied Sciences, Free Full-Text
![From GAN to WGAN](https://www.oreilly.com/api/v2/epubs/9781492041931/files/assets/gedl_0418.png)
4. Generative Adversarial Networks - Generative Deep Learning [Book]
![From GAN to WGAN](https://www.oreilly.com/api/v2/epubs/9781492041931/files/assets/gedl_0408.png)
4. Generative Adversarial Networks - Generative Deep Learning [Book]
![From GAN to WGAN](https://ar5iv.labs.arxiv.org/html/1705.02438/assets/GAN_fig2.png)
1705.02438] Face Super-Resolution Through Wasserstein GANs
![From GAN to WGAN](https://i.imgur.com/WdUTLLz.png)
GANs in PyTorch: DCGAN, cGAN, LSGAN, InfoGAN, WGAN and more - CV Notes
depuis
par adulte (le prix varie selon la taille du groupe)