Enhancing GAN Stability with Wasserstein Loss and Gradient Penalty

Generative Adversarial Networks (GANs) are widely used to model complex data distributions, but traditional GANs, particularly those using Binary Cross-Entropy (BCE) loss, face significant issues that hinder effective training. In this article, we’ll...