A Theoretical Analysis of Out-of-Distribution Detection in Multi-Label Classification

Author:

Zhang Dell1ORCID,Taneva-Popova Bilyana2ORCID

Affiliation:

1. Thomson Reuters Labs, London, United Kingdom

2. Thomson Reuters Labs, Zug, Switzerland

Publisher

ACM

Reference75 articles.

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3. Bertrand Charpentier , Daniel Zügner , and Stephan Günnemann . 2020 . Posterior Network : Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts . In Advances in Neural Information Processing Systems , Vol. 33 . Curran Associates, Inc., 1356--1367. Bertrand Charpentier, Daniel Zügner, and Stephan Günnemann. 2020. Posterior Network : Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts. In Advances in Neural Information Processing Systems, Vol. 33. Curran Associates, Inc., 1356--1367.

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5. Deep Integration: A Multi-Label Architecture for Road Scene Recognition

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1. Asymmetric Beta Loss for Evidence-Based Safe Semi-Supervised Multi-Label Learning;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

2. Multi-label Out-of-Distribution Detection with Spectral Normalized Joint Energy;Lecture Notes in Computer Science;2024

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