Learning to predict defect structures

[tomasfbouvier]

For my project we need to predict properly defects e.g self interstitials, vacancies, dumbells etc. Those structures are defined as defects within a non defected structure. For example in Silicon a self interstitial represents a single atom within a pristine diamond lattice. In the training sets it is usual to see structures of more than 200 atoms among which only one is relevant. This makes the formation energy of the defect difficult to learn and currently NEP performs worse than GAP in prediciting them (for Si). Would it be possible to implement a special computation routine of the energy loss function for those cases taking into account not only the defected structure but also the reference lattice?
L = ( E(N+n)- Et(N+n) - (1+n/N)(E(N) - Et(N))/n where N is the number of atoms in the reference cell, n the number of atoms in the defect, L the corresponding loss to the structure and E and Et the predicted and ground training energies respectively