Machine Learning, Deep Learning, Generative Model, Adversarial Network, Autoencoder.
why Adversarial networks are better at producing realistic images. But there are problems with GANs such as stabilizing their training which is still an active area of research. However GANs are really powerful and currently they are being used in a variety of tasks such as high quality image (see