New publication - Circumventing data imbalance in magnetic ground state data for magnetic moment predictions

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Modeling magnetic materials with DFT is hard. In this work we develop a machine learning approach to predicting magnetic properties of materials based on their structure. Our two stage model first predicts if a material is magnetic, and then if it is, what the magnetic moments on each atom are. We show this can lead to faster and lower energy DFT solutions.

  author =       {Rohan Yuri Sanspeur and John R Kitchin},
  title =        {Circumventing Data Imbalance in Magnetic Ground State Data for
                  Magnetic Moment Predictions},
  journal =      {Machine Learning: Science and Technology},
  volume =       {5},
  number =       {1},
  pages =        {015023},
  year =         2024,
  doi =          {10.1088/2632-2153/ad23fb},
  url =          {},
  DATE_ADDED =   {Tue Feb 6 20:13:47 2024},

Copyright (C) 2024 by John Kitchin. See the License for information about copying.

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