A novel physics-regularized interpretable machine learning model for grain growth

  • Weishi Yan
  • , Joseph Melville
  • , Vishal Yadav
  • , Kristien Everett
  • , Lin Yang
  • , Michael S. Kesler
  • , Amanda R. Krause
  • , Michael R. Tonks
  • , Joel B. Harley

Research output: Contribution to journal › Article › peer-review

24 Scopus citations

Fingerprint

Dive into the research topics of 'A novel physics-regularized interpretable machine learning model for grain growth'. Together they form a unique fingerprint.
Sort by

Engineering

Material Science