Hamiltonian Learning for Excited States.
The repository contains scripts and examples to build indirect ML models that predict an effective single-particle Hamiltonian, and train against reference electronic structure calculations of either the matrix elements themselves, or derived quantities such as the electronic eigenvalues or the Löwdin charges.