In the initial experimental phase, we constructed models using the aforementioned graph convolutional operators: MF, GIN, GINE, and GATV2 (S.4). Each model consisted of n convolutional layers of size m, followed by batch normalization and LeakyReLU activation , except after the final convolutional layer. The classification module consisted of a fully connected layer of size s, batch normalization, LeakyReLU activation, and a final fully connected layer followed by a sigmoid activation, mapping the latent representation to a probabilistic binary output.