3 papers
cs.LG2025
Global explainability of a deep abstaining classifier
Sayera Dhaubhadel, Jamaludin Mohd-Yusof, Benjamin H. McMahon +8
We present a global explainability method to characterize sources of errors in the histology prediction task of our real-world multitask convolutional neural network (MTCNN)-based…
cond-mat.mtrl-sci2020
Uncertainty Bounds for Multivariate Machine Learning Predictions on High-Strain Brittle Fracture
Cristina Garcia-Cardona, M. Giselle Fernández-Godino, Daniel O'Malley +1
Simulation of the crack network evolution on high strain rate impact experiments performed in brittle materials is very compute-intensive. The cost increases even more if multiple…
cs.LG2020
Why I'm not Answering: Understanding Determinants of Classification of an Abstaining Classifier for Cancer Pathology Reports
Sayera Dhaubhadel, Jamaludin Mohd-Yusof, Kumkum Ganguly +13
Safe deployment of deep learning systems in critical real world applications requires models to make very few mistakes, and only under predictable circumstances. In this work, we a…