Out-Of-Distribution Detection with Diversification (Provably)

Neural Information Processing Systems 

Out-of-distribution (OOD) detection is crucial for ensuring reliable deployment of machine learning models. Recent advancements focus on utilizing easily accessible auxiliary outliers (e.g., data from the web or other datasets) in training.

Similar Docs  Excel Report  more

TitleSimilaritySource
None found