226 citations · 619 across the 10 of their papers we have counts for
4 papers · 1 filter
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…
Robust FCC solute diffusion predictions from ab-initio machine learning methods
Henry Wu, Aren Lorenson, Ben Anderson +4
We evaluate the performance of four machine learning methods for modeling and predicting FCC solute diffusion barriers. More than 200 FCC solute diffusion barriers from previous de…
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…