180 citations · 276 across the 6 of their papers we have counts for
6 papers
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…
Machine-learned metrics for predicting the likelihood of success in materials discovery
Yoolhee Kim, Edward Kim, Erin Antono +2
Materials discovery is often compared to the challenge of finding a needle in a haystack. While much work has focused on accurately predicting the properties of candidate materials…
Assessing the Frontier: Active Learning, Model Accuracy, and Multi-objective Materials Discovery and Optimization
Zachary del Rosario, Matthias Rupp, Yoolhee Kim +2
Discovering novel materials can be greatly accelerated by iterative machine learning-informed proposal of candidates---active learning. However, standard \emph{global-scope error}…
Overcoming data scarcity with transfer learning
Maxwell L. Hutchinson, Erin Antono, Brenna M. Gibbons +3
Despite increasing focus on data publication and discovery in materials science and related fields, the global view of materials data is highly sparse. This sparsity encourages tra…
Building Data-driven Models with Microstructural Images: Generalization and Interpretability
Julia Ling, Maxwell Hutchinson, Erin Antono +3
As data-driven methods rise in popularity in materials science applications, a key question is how these machine learning models can be used to understand microstructure. Given the…
High-Dimensional Materials and Process Optimization using Data-driven Experimental Design with Well-Calibrated Uncertainty Estimates
Julia Ling, Max Hutchinson, Erin Antono +2
The optimization of composition and processing to obtain materials that exhibit desirable characteristics has historically relied on a combination of scientist intuition, trial and…