48 citations · 63 across the 2 of their papers we have counts for
3 papers
Quantifying the performance of machine learning models in materials discovery
Christopher K. H. Borg, Eric S. Muckley, Clara Nyby +4
The predictive capabilities of machine learning (ML) models used in materials discovery are typically measured using simple statistics such as the root-mean-square error (RMSE) or…
Mapping Thermoelectric Transport in a Multicomponent Alloy Space
Ramya Gurunathan, Suchismita Sarker, Christopher K. H. Borg +4
Interest in high entropy alloy thermoelectric materials is predicated on achieving ultralow lattice thermal conductivity through large compositional disorder. However, h…
Quantifying uncertainty in high-throughput density functional theory: a comparison of AFLOW, Materials Project, and OQMD
Vinay I. Hegde, Christopher K. H. Borg, Zachary del Rosario +7
A central challenge in high throughput density functional theory (HT-DFT) calculations is selecting a combination of input parameters and post-processing techniques that can be use…