CAN (Creative Adversarial Network) -- Explained – Harshvardhan Gupta – Medium

GAN's consists of two competing neural networks, namely the Generator and the Discriminator. As is suggestive of the name, the Generator is responsible for generating data from some input (this input can be noise or even some other data). The discriminator is then responsible for analysing that data and discriminating wether that data was real(if it came from our dataset) or if its fake(if it came from the generator). If the above equation was too complex for you, you are not alone. I will go through this equation step by step and explain what each component means.