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cs.LG2026
Equivariant Deep Learning in Direct-Product Space for Electronic-Structure Hamiltonian Prediction
Shi Yin, Zujian Dai, Xinyang Pan +1
Most existing equivariant architectures for Hamiltonian prediction propagate features in direct-sum spaces of irreducible spherical tensors, whereas the target Hamiltonian is natur…
cs.LG2025
Advancing Universal Deep Learning for Electronic-Structure Hamiltonian Prediction of Materials
Shi Yin, Zujian Dai, Xinyang Pan +1
Deep learning methods for electronic-structure Hamiltonian prediction has offered significant computational efficiency advantages over traditional DFT methods, yet the diversity of…
cs.LG2024★ 2 cited
TraceGrad: a Framework Learning Expressive SO(3)-equivariant Non-linear Representations for Electronic-Structure Hamiltonian Prediction
Shi Yin, Xinyang Pan, Fengyan Wang +1
We propose a framework to combine strong non-linear expressiveness with strict SO(3)-equivariance in prediction of the electronic-structure Hamiltonian, by exploring the mathematic…