47 citations · 111 across the 9 of their papers we have counts for
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physics.comp-ph2019★ 47 cited
Predicting Compressive Strength of Consolidated Molecular Solids Using Computer Vision and Deep Learning
Brian Gallagher, Matthew Rever, Donald Loveland +6
We explore the application of computer vision and machine learning (ML) techniques to predict material properties (e.g. compressive strength) based on SEM images. We show that it's…
physics.comp-ph2019★ 1 cited
Reliable and Explainable Machine Learning Methods for Accelerated Material Discovery
Bhavya Kailkhura, Brian Gallagher, Sookyung Kim +2
Material scientists are increasingly adopting the use of machine learning (ML) for making potentially important decisions, such as, discovery, development, optimization, synthesis…