 Causal relations have indeed the great potential of being generalizable.Variational autoencoder models make strong assumptions concerning the distribution of "latent variables".They use a variational approach for latent representation learning, which results in an additional loss component and a specific estimator for the training algorithm called the Stochastic Gradient Variational Bayes (SGVB) estimator.