Each graph edge attention layer performs a non-linear transform and mixing operation between nodes connected by edges. The embedded edges, e ′ ij , are transformed to create attention scores that determine the degree of mixing between nodes along each attention head. Here, each EGAT layer has four heads, meaning that the embedded 512x1 node feature vector, n ′ i , is reshaped into four 128x1 vectors, n ′,h i , each of which is mixed with the corresponding reshaped vectors of neighboring nodes, n ′,h j , based on the attention values of each head, α h ij . The mathematical description of these steps is as follows.