In the latent space 𝒁, the generator 𝑮 𝑿→𝒁 (𝒙) takes the training set coordinates 𝒙 as an input and attempts to generate pseudo-latent variable 𝒛′ that involve an indistinguishable statistical distribution from that of the latent variable 𝒛. The discriminator 𝑫 𝒁 is a binary classifier trained to differentiate 𝒛 and 𝒛′. The loss functions for the generator and discriminator in the latent space are: