Fig. 7: Visual representation of the two neural network architecture types.
From: Training data selection for accuracy and transferability of interatomic potentials
A type A step-down and B type B expand-and-contract. The input is a vector of D descriptors of the atomic environment of one atom. These are passed through each layer in the network to yield the atomic energy Ei of the atom. Integer factors indicate the number of nodes in each layer. The total number of nodes defines the number of degree of freedom NDoF for each model. Recall from Fig. 3 that D is 14, 30, or 55. Notice that D only affects the nodes in the input layer since the nodes on the other layers remain unchanged.
