Covers the precursors of Kohn-Sham Density Functional Theory (DFT) and the Kohn-Sham formulation, explaining types of Exc[p] approximations and the performance of LDA.
Explores the integration of machine learning into discrete choice models, emphasizing the importance of theory constraints and hybrid modeling approaches.
