ChIMES models view system configurations as a collection of fully connected graphs between atoms in n-body clusters, where atoms form nodes and the transformed distances between those atoms form the edges. We refer to these cluster graphs as the ChIMES descriptor. The parametric linearity characteristic to ChIMES models coupled with use of a cluster-centered many-body descriptor gives rise to an inherently hierarchical parameter structure that can be leveraged for transfer learning. Specifically, the atom cluster energy terms given in Eq. 1 can be further decomposed based on constituent atom types. For example, the two-body energy contributions for a system comprised entirely of C and N can be written as: