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The multi-mesh adjacency matrix (node edges) and node features are used as the inputs to a graph autoencoder. The GNN uses an MSE loss derived from the comparisons on the differences of the input and output node features for unsupervised training. After training, the latent space representation outputs (orange) from the encoder can be used for vector-based similarity comparisons.

DOI