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Citrine Informatics (United States)

United States

3 papers here79 citations across 3
fields
  • cond-mat.mtrl-sci2
  • cs.AI1
ROR 04wka5f51OpenAlex

affiliations via OpenAlex

most citedRobust FCC solute diffusion predictions from ab-initio machine learning methods

71 citations

researchers with a paper here
  • B. Meredig3 · h 32
  • Erin Antono2 · h 13
  • Julia Ling2 · h 10
  • A. Lorenson1 · h 3
  • B. Anderson1 · h 6
  • Brian DeCost1 · h 9
  • D. Morgan1 · h 72
  • Edward Kim1
  • E. Holm1 · h 43
  • Hao Wu1 · h 3
  • He-Jhen Wu1 · h 1
  • L. Witteman1 · h 6
collaborating institutions
  • Carnegie Mellon UniversityUS1 paper
  • University of Wisconsin–MadisonUS1 paper
Showing cond-mat.mtrl-sciShow all

2 papers · 1 filter

cond-mat.mtrl-sci2019★ 2 cited

Machine-learned metrics for predicting the likelihood of success in materials discovery

Yoolhee Kim, Edward Kim, Erin Antono +2

Materials discovery is often compared to the challenge of finding a needle in a haystack. While much work has focused on accurately predicting the properties of candidate materials…

cond-mat.mtrl-sci2017★ 71 cited

Robust FCC solute diffusion predictions from ab-initio machine learning methods

Henry Wu, Aren Lorenson, Ben Anderson +4

We evaluate the performance of four machine learning methods for modeling and predicting FCC solute diffusion barriers. More than 200 FCC solute diffusion barriers from previous de…

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