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In this video we implement WGAN and WGAN-GP in PyTorch. Both of these improvements are based on the loss function of GANs and focused specifically on improving the stability of training.

Github Repository:
https://github.com/aladdinpersson/Machine-Learning-Collection

OUTLINE:

0:00 - Introduction
0:27 - Understanding WGAN
6:53 - WGAN Implementation details
9:15 - Coding WGAN
15:50 - Understanding WGAN-GP
18:48 - Coding WGAN-GP
25:29 - Ending

#pytorch #deep-learning #python #artificial-intelligence #developer

Wasserstein Generative Adversarial Networks (WGAN & WGAN-GP) in PyTorch

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Wasserstein Generative Adversarial Networks (WGAN & WGAN-GP) in PyTorch

Wasserstein Generative Adversarial Networks (WGAN & WGAN-GP) in PyTorch. We implement WGAN and WGAN-GP in PyTorch. Both of these improvements are based on the loss function of GANs and focused specifically on improving the stability of training.

4.50 GEEK