112 citations · 198 across the 6 of their papers we have counts for
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cond-mat.mtrl-sci2023★ 23 cited
Reproducibility in Computational Materials Science: Lessons from 'A General-Purpose Machine Learning Framework for Predicting Properties of Inorganic Materials'
Daniel Persaud, Logan Ward, Jason Hattrick-Simpers
The integration of machine learning techniques in materials discovery has become prominent in materials science research and has been accompanied by an increasing trend towards ope…
cond-mat.mtrl-sci2023★ 112 cited
On the redundancy in large material datasets: efficient and robust learning with less data
Kangming Li, Daniel Persaud, Kamal Choudhary +3
Extensive efforts to gather materials data have largely overlooked potential data redundancy. In this study, we present evidence of a significant degree of redundancy across multip…