49 citations · 61 across the 12 of their papers we have counts for
4 papers · 1 filter
Leveraging Uncertainty from Deep Learning for Trustworthy Materials Discovery Workflows
Jize Zhang, Bhavya Kailkhura, T. Yong-Jin Han
In this paper, we leverage predictive uncertainty of deep neural networks to answer challenging questions material scientists usually encounter in machine learning based materials…
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…
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning
Jize Zhang, Bhavya Kailkhura, T. Yong-Jin Han
This paper studies the problem of post-hoc calibration of machine learning classifiers. We introduce the following desiderata for uncertainty calibration: (a) accuracy-preserving,…