Yuxin Ge

CESED: Exploiting Hyperspherical Predefined Evenly-Distributed Class Centroids for OOD Detection

2023 · Society for Industrial and Applied Mathematics eBooks

Out-of-distribution (OOD) detection is critical for ensuring the safe deployment of machine learning models in the open world. Due to the simplicity and intuitiveness of distance- based methods, i.e., samples are detected as OOD if …

READ: Aggregating Reconstruction Error into Out-of-Distribution Detection

2023 · Proceedings of the AAAI Conference on Artificial Intelligence

Detecting out-of-distribution (OOD) samples is crucial to the safe deployment of a classifier in the real world. However, deep neural networks are known to be overconfident for abnormal data. Existing works directly design score function …