Michael Greenwood

Most-cited papers

1. A critical examination of robustness and generalizability of machine learning prediction of materials properties

   Kangming Li, Brian L. DeCost, Kamal Choudhary, Michael Greenwood +1 more

   2022npj Computational Materials164 citations Open access

   Semantic Scholar

   Save

2. Exploiting redundancy in large materials datasets for efficient machine learning with less data

   Kangming Li, D. Persaud, Kamal Choudhary, Brian L. DeCost +2 more

   2023Nature Communications123 citations Open access

   Semantic Scholar

   Save

3. Efficient first principles based modeling via machine learning: from simple representations to high entropy materials

   Kangming Li, Kamal Choudhary, Brian L. DeCost, Michael Greenwood +1 more

   2024Journal of Materials Chemistry A16 citations Open access

   Semantic Scholar

   Save

4. A call for caution in the era of AI-accelerated materials science

   Kangming Li, Edward Kim, Yao Fehlis, D. Persaud +3 more

   2023Matter3 citations Open access

   Semantic Scholar

   Save

5. Publisher Correction: Exploiting redundancy in large materials datasets for efficient machine learning with less data

   Kangming Li, D. Persaud, Kamal Choudhary, Brian L. DeCost +2 more

   2024Nature Communications0 citations Open access

   Semantic Scholar

   Save

6. Prediction Robustness and Data Redundancy in Machine Learning for Materials Science

   Kangming Li, D. Persaud, Kamal Choudhary, Brian L. DeCost +2 more

   2023Proceedings of the MATSUS Spring 2024 Conference0 citations

   Semantic Scholar

   Save