Here, µτ and Στ represent the output of the variational encoder, whose parameter is τ . The sampling step in ( ) is implemented based on the reparameterization trick . In the training phase, this step works as a kind of data augmentation, which introduces some randomness in the graph-level embedding and thus suppresses the overfitting risk. In the testing phase, we set the mean vector µτ (hs) as the embedding zs for a deterministic output.