Out-of-distribution

Understanding Out-of-Distribution Accuracies through Quantifying Difficulty of Test Samples

Existing works show that although modern neural networks achieve remarkable generalization performance on the in-distribution (ID) dataset, the accuracy drops significantly on the out-of-distribution (OOD) datasets …