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SC-MIL: Supervised Contrastive Multiple Instance Learning for Imbalanced Classification in Pathology., , , , , , , , and . CoRR, (2023)Self-training of Machine Learning Models for Liver Histopathology: Generalization under Clinical Shifts., , , , , , , , , and . CoRR, (2022)ContriMix: Unsupervised disentanglement of content and attribute for domain generalization in microscopy image analysis., , , , , , , , , and 2 other author(s). CoRR, (2023)Additive MIL: Intrinsic Interpretability for Pathology., , , , , and . CoRR, (2022)Rethinking Machine Learning Model Evaluation in Pathology., , , , , and . CoRR, (2022)Additive MIL: Intrinsically Interpretable Multiple Instance Learning for Pathology., , , , , and . NeurIPS, (2022)SC-MIL: Supervised Contrastive Multiple Instance Learning for Imbalanced Classification in Pathology., , , , , , , , and . WACV, page 7931-7940. IEEE, (2024)Synthetic DOmain-Targeted Augmentation (S-DOTA) Improves Model Generalization in Digital Pathology., , , , , , , , , and 13 other author(s). CoRR, (2023)