The vertex pre-processing specifically includes an atomic feature embedding block that projects the atomic number into a learnt embedded feature vector using a "lookup" function in a similar fashion to . This embedding model allows for semantic relationships between atomic species to be learned and represented meaningfully in higher-dimensional vector spaces. The edge pairwise-distance features are projected onto k evenly-spaced Gaussian radial basis functions to help decorrelate the input as suggested by . The k th element of our new edge features e 0 ij then becomes