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cs.LG2025
Learning to Detect Label Errors by Making Them: A Method for Segmentation and Object Detection Datasets
Sarina Penquitt, Tobias Riedlinger, Timo Heller +2
Recently, detection of label errors and improvement of label quality in datasets for supervised learning tasks has become an increasingly important goal in both research and indust…
cs.LG2023★ 1 cited
LU-Net: Invertible Neural Networks Based on Matrix Factorization
Robin Chan, Sarina Penquitt, Hanno Gottschalk
LU-Net is a simple and fast architecture for invertible neural networks (INN) that is based on the factorization of quadratic weight matrices , where is…