EperLuo/PubChemQH

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The declared licence (mit) is classified as permissive.

Declared licence: mit, from the tagEvidence: README.md at c462018
Licence files: No licence file at the top level of the repositoryEvidence: file list at c462018
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

Each cell links to what was checked: a file, a file list or a Hub record.

Citation text from the card

@InProceedings{pmlr-v267-luo25l,
  title = 	 {Efficient and Scalable Density Functional Theory {H}amiltonian Prediction through Adaptive Sparsity},
  author =       {Luo, Erpai and Wei, Xinran and Huang, Lin and Li, Yunyang and Yang, Han and Xia, Zaishuo and Wang, Zun and Liu, Chang and Shao, Bin and Zhang, Jia},
  booktitle = 	 {Proceedings of the 42nd International Conference on Machine Learning},
  pages = 	 {41368--41390},
  year = 	 {2025},
  volume = 	 {267},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {13--19 Jul},
  publisher =    {PMLR},
  pdf = 	 {https://raw.githubusercontent.com/mlresearch/v267/main/assets/luo25l/luo25l.pdf},
  url = 	 {https://proceedings.mlr.press/v267/luo25l.html}
}

@inproceedings{
li2025enhancing,
title={Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems},
author={Yunyang Li and Zaishuo Xia and Lin Huang and Xinran Wei and Samuel Harshe and Han Yang and Erpai Luo and Zun Wang and Jia Zhang and Chang Liu and Bin Shao and Mark Gerstein},
booktitle={The Thirteenth International Conference on Learning Representations},
year={2025},
url={https://openreview.net/forum?id=twEvvkQqPS}
}

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dataset_licence({ "id": "EperLuo/PubChemQH" })
signal: "permissive"
stated_licence: "mit"
sources: 0