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On the Scale Invariance in State of the Art CNNs Trained on ImageNet., , , , and . Mach. Learn. Knowl. Extr., 3 (2): 374-391 (2021)Shifts 2.0: Extending The Dataset of Real Distributional Shifts., , , , , , , , , and 8 other author(s). CoRR, (2022)Regression Concept Vectors for Bidirectional Explanations in Histopathology., , and . MLCN/DLF/iMIMIC@MICCAI, volume 11038 of Lecture Notes in Computer Science, page 124-132. Springer, (2018)A global taxonomy of interpretable AI: unifying the terminology for the technical and social sciences., , , , , , , , , and 6 other author(s). Artif. Intell. Rev., 56 (4): 3473-3504 (April 2023)Reference Exascale Architecture (Extended Version)., , , , , , , , , and 1 other author(s). Comput. Informatics, 39 (4): 644-677 (2020)Guiding CNNs towards Relevant Concepts by Multi-task and Adversarial Learning., , , and . CoRR, (2020)Regression Concept Vectors for Bidirectional Explanations in Histopathology., , and . CoRR, (2019)Tackling Bias in the Dice Similarity Coefficient: Introducing NDSC for White Matter Lesion Segmentation., , , , , , and . ISBI, page 1-5. IEEE, (2023)Sharpening Local Interpretable Model-Agnostic Explanations for Histopathology: Improved Understandability and Reliability., , , , , and . MICCAI (3), volume 12903 of Lecture Notes in Computer Science, page 540-549. Springer, (2021)Regression-based Deep-Learning predicts molecular biomarkers from pathology slides., , , , , , , , , and 7 other author(s). CoRR, (2023)