Data Science, Machine Learning, Deep Learning, Artificial Intelligence, Computer Vision.
structure of the distributions. In the context of GANs, the Wasserstein distance is used as a metric to measure the difference between the real data distribution and the generated data distribution. In WGAN, the critic network is trained to estimate the Wasserstein distance between the real data