Bin Shao

Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems

Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity

SE3Set: Harnessing equivariant hypergraph neural networks for molecular representation learning

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation

Neural P$^3$M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs

Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models