A Deep-Learning Architecture of Range-Separated Hybrid Functional Optimization Method

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A deep learning framework for predicting molecular Hamiltonians using Graph Neural Networks (GNNs) with equivariant message passing.(Basic Framework)

This is a project for optimization of Exchange-Correlation Functionals in LR-TDDFT calculations.