Machine Learning, Deep Learning, Generative Model, Adversarial Network, Autoencoder.
between k steps of optimizing D and one step of optimizing G on the mini-batch. The process of training stops when the Discriminator is unable to distinguish ρg and ρdata i.e. D(x, өd) = ½ or when ρg = ρdata. One of the earliest model on GAN employing Convolutional Neural Network was DCGAN which