most citedExplaining Neural Network Predictions for Functional Data Using Principal Component Analysis and Feature Importance

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cs.LG2023

Comparing the quality of neural network uncertainty estimates for classification problems

Daniel Ries, Joshua Michalenko, Tyler Ganter +2

Traditional deep learning (DL) models are powerful classifiers, but many approaches do not provide uncertainties for their estimates. Uncertainty quantification (UQ) methods for DL…

cs.LG2020★ 2 cited

Explaining Neural Network Predictions for Functional Data Using Principal Component Analysis and Feature Importance

Katherine Goode, Daniel Ries, Joshua Zollweg

Optical spectral-temporal signatures extracted from videos of explosions provide information for identifying characteristics of the corresponding explosive devices. Currently, the…