no code implementations • 29 Sep 2021 • Jeong-Hyeon Moon, Namhyuk Ahn, Kyung-Ah Sohn
Out-of-distribution (OOD) detection has made significant progress in recent years because the distribution mismatch between the training and testing can severely deteriorate the reliability of a machine learning system. Nevertheless, the lack of precise interpretation of the in-distribution limits the application of OOD detection methods to real-world system pipielines.
Out-of-Distribution Detection Out of Distribution (OOD) Detection +1
1 code implementation • 20 Apr 2021 • JuneKyu Park, Jeong-Hyeon Moon, Namhyuk Ahn, Kyung-Ah Sohn
From a safety perspective, a machine learning method embedded in real-world applications is required to distinguish irregular situations.