Machine Learning, Artificial Intelligence, Graph Neural Networks, Deep Learning, Data Science.
reconstructs the data. If the reconstructed data X is very different than the original data, then the reconstruction loss will be high. The second part of the loss function works as a regularizer. It is the KL-divergence of the approximate from the true posterior (p(z)), which measures how closely