Projecting pre-trained image features into hyperbolic space and classifying them with a learned hyperplane improves medical anomaly detection AUROC over Euclidean baselines on BMAD benchmarks.
In: Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (2022)
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Is Hyperbolic Space All You Need for Medical Anomaly Detection?
Projecting pre-trained image features into hyperbolic space and classifying them with a learned hyperplane improves medical anomaly detection AUROC over Euclidean baselines on BMAD benchmarks.