He Li

Orcid: 0000-0002-5967-5251

Affiliations:
  • Tsinghua University, Institute for Advanced Study, Department of Physics, State Key Laboratory of Low Dimensional Quantum Physics, Beijing, China


According to our database1, He Li authored at least 12 papers between 2022 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

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Article 
PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2024
Author Correction: Deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation.
Nat. Comput. Sci., November, 2024

2023
Code for "General framework for E(3)-equivariant neural network representation of density functional theory Hamiltonian".
Dataset, March, 2023

Code for deep-learning electronic-structure calculation of magnetic superstructures.
Dataset, February, 2023

Dataset for deep-learning electronic-structure calculation of magnetic superstructures.
Dataset, February, 2023

Dataset3 for "General framework for E(3)-equivariant neural network representation of density functional theory Hamiltonian".
Dataset, January, 2023

Dataset2 for "General framework for E(3)-equivariant neural network representation of density functional theory Hamiltonian".
Dataset, January, 2023

Dataset1 for "General framework for E(3)-equivariant neural network representation of density functional theory Hamiltonian".
Dataset, January, 2023

Author Correction: Deep-learning electronic-structure calculation of magnetic superstructures.
Nat. Comput. Sci., 2023

Deep-learning electronic-structure calculation of magnetic superstructures.
Nat. Comput. Sci., 2023

2022
Code for deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation.
Dataset, May, 2022

Dataset for deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation.
Dataset, May, 2022

Deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation.
Nat. Comput. Sci., 2022


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