47 citations · 122 across the 11 of their papers we have counts for
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cs.LG2019★ 32 cited
Generative Counterfactual Introspection for Explainable Deep Learning
Shusen Liu, Bhavya Kailkhura, Donald Loveland +1
In this work, we propose an introspection technique for deep neural networks that relies on a generative model to instigate salient editing of the input image for model interpretat…
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…