4 papers
Mapping DNN Embedding Manifolds for Network Generalization Prediction
Molly O'Brien, Julia Bukowski, Mathias Unberath +2
Understanding Deep Neural Network (DNN) performance in changing conditions is essential for deploying DNNs in safety critical applications with unconstrained environments, e.g., pe…
Network Generalization Prediction for Safety Critical Tasks in Novel Operating Domains
Molly O'Brien, Mike Medoff, Julia Bukowski +1
It is well known that Neural Network (network) performance often degrades when a network is used in novel operating domains that differ from its training and testing domains. This…
Robotic Surgery With Lean Reinforcement Learning
Yotam Barnoy, Molly O'Brien, Will Wang +1
As surgical robots become more common, automating away some of the burden of complex direct human operation becomes ever more feasible. Model-free reinforcement learning (RL) is a…
Dependable Neural Networks for Safety Critical Tasks
Molly O'Brien, William Goble, Greg Hager +1
Neural Networks are being integrated into safety critical systems, e.g., perception systems for autonomous vehicles, which require trained networks to perform safely in novel scena…