PyTorch implementations of Generative Adversarial Networks.
Role in this project:
ML Engineer Contributions:9 commits, 1 PR, 2 comments in 9 days
Contributions summary:Yutong implemented and refined a Wasserstein GAN with a divergence penalty (WGAN-div) model in PyTorch within this repository. Their contributions included defining the model architecture, loss functions, and training loops. Subsequent commits addressed formatting issues and corrected bugs to ensure proper GPU execution.
generative-adversarial-networkpytorch
Contributions:23 commits, 20 pushes, 1 branch in 9 months