5 citations · 7 across the 2 of their papers we have counts for
3 papers
Explainable Deep Learning for Uncovering Actionable Scientific Insights for Materials Discovery and Design
Shusen Liu, Bhavya Kailkhura, Jize Zhang +4
The scientific community has been increasingly interested in harnessing the power of deep learning to solve various domain challenges. However, despite the effectiveness in buildin…
Actionable Attribution Maps for Scientific Machine Learning
Shusen Liu, Bhavya Kailkhura, Jize Zhang +4
The scientific community has been increasingly interested in harnessing the power of deep learning to solve various domain challenges. However, despite the effectiveness in buildin…
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…