CASE: Exploiting Intra-class Compactness and Inter-class Separability of Feature Embeddings for Out-of-Distribution Detection
Detecting out-of-distribution (OOD) inputs is critical for reliable machine learning, but deep
neural networks often make overconfident predictions, even for OOD inputs that deviate from …
neural networks often make overconfident predictions, even for OOD inputs that deviate from …