no code implementations • 3 Feb 2022 • Molly O'Brien, Julia Bukowski, Mathias Unberath, Aria Pezeshk, Greg Hager
Understanding Deep Neural Network (DNN) performance in changing conditions is essential for deploying DNNs in safety critical applications with unconstrained environments, e. g., perception for self-driving vehicles or medical image analysis.
no code implementations • 17 Aug 2021 • Molly O'Brien, Mike Medoff, Julia Bukowski, Greg Hager
We propose the task Network Generalization Prediction: predicting the expected network performance in novel operating domains.
no code implementations • 20 Dec 2019 • Molly O'Brien, William Goble, Greg Hager, Julia Bukowski
Our results demonstrate that we can accurately predict the ML Dependability, Task Undependability, and Harmful Undependability for operating conditions that are significantly different from the testing conditions.