Out-of-Distribution (OOD) Data

OOD data represents samples that differ significantly from the distribution of the training data. These samples can lead to unreliable predictions and should be detected and handled appropriately. Detection methods include density estimation uncertainty quantification and ensemble disagreement analysis.

Autonomous systems medical imaging robotic control