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Orbital Research (United States)

United States

1 paper here203 citations across 1
fields
  • cond-mat.mtrl-sci1
ROR 00rbdbh54OpenAlex

affiliations via OpenAlex

most citedA practical guide to machine learning interatomic potentials -- Status and future

203 citations

researchers with a paper here
  • Aidan Thompson1 · h 1
  • Anders Johansson1 · h 6
  • B. Blaiszik1 · h 32
  • Boris Kozinsky1 · h 8
  • Bowen Deng1 · h 10
  • Brandon M. Wood1 · h 2
  • Chen Shen1 · h 3
  • Clare Yijia Xie1 · h 2
  • Dane Morgan1 · h 2
  • E. D. Cubuk1 · h 55
  • G. Ceder1 · h 159
  • G. Csányi1 · h 9
collaborating institutions
  • Argonne National LaboratoryUS1 paper
  • Carnegie Mellon UniversityUS1 paper
  • Google (United States)US1 paper
  • Harvard UniversityUS1 paper
  • Harvard University PressUS1 paper
  • Lawrence Berkeley National LaboratoryUS1 paper
  • Material Measurement LaboratoryUS1 paper
  • National Institute of Standards and TechnologyUS1 paper
  • Pennsylvania State UniversityUS1 paper
  • Ruhr University BochumDE1 paper
  • Tata Institute of Fundamental ResearchIN1 paper
  • University of California, BerkeleyUS1 paper

1 paper

cond-mat.mtrl-sci2025★ 203 cited

A practical guide to machine learning interatomic potentials -- Status and future

Ryan Jacobs, Dane Morgan, Siamak Attarian +27

The rapid development and large body of literature on machine learning interatomic potentials (MLIPs) can make it difficult to know how to proceed for researchers who are not exper…

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