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Daniel S. King — most-cited papers & profile · AI for Science
← authors
·
overview
Daniel S. King
3
papers ·
37
citations
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
A universal augmentation framework for long-range electrostatics in machine learning interatomic potentials
2025 · 24 citations
Machine learning interatomic potential can infer electrical response
2025 · 11 citations
Learning charges and long-range interactions from energies and forces
2024 · 2 citations
Top co-authors
Dongjin Kim
· 2
Peichen Zhong
· 2
Bingqing Cheng
· 1
Bingqing Cheng
· 1
Bingqing Cheng
· 1
Dongjin Kim
· 1
Peichen Zhong
· 1
Theo Jaffrelot Inizan
· 1
Xiaoyu Wang
· 1
Topics
Materials
Chemistry
Physics ML