 It assumes that the data is generated by a directed graphical model formula_62 and that the encoder is learning an approximation formula_63 to the posterior distribution formula_64 where formula_65 and formula_66 denote the parameters of the encoder (recognition model) and decoder (generative model) respectively.The probability distribution of the latent vector of a VAE typically matches that of the training data much closer than a standard autoencoder.The objective of VAE has the following form