Mandala is a modular E(3)-equivariant GNN framework that learns sparse DFT Hamiltonian, overlap, and density matrices and supervises them with operator-derived observables.
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MANDALA: An E(3)-Equivariant Graph Neural Network Framework for Learning Electronic-Structure Operators with Observable Guidance
Mandala is a modular E(3)-equivariant GNN framework that learns sparse DFT Hamiltonian, overlap, and density matrices and supervises them with operator-derived observables.