8 citations · 10 across the 3 of their papers we have counts for
Showing cond-mat.mtrl-sciShow all
2 papers · 1 filter
cond-mat.mtrl-sci2023★ 1 cited
Transfer learning on large datasets for the accurate prediction of material properties
Noah Hoffmann, Jonathan Schmidt, Silvana Botti +1
Graph neural networks trained on large crystal structure databases are extremely effective in replacing ab initio calculations in the discovery and characterization of materials. H…
cond-mat.mtrl-sci2022★ 8 cited
Large-scale machine-learning-assisted exploration of the whole materials space
Jonathan Schmidt, Noah Hoffmann, Hai-Chen Wang +5
Crystal-graph attention networks have emerged recently as remarkable tools for the prediction of thermodynamic stability and materials properties from unrelaxed crystal structures.…