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Debiasing Counterfactuals in the Presence of Spurious Correlations.

, , , , , , и . CLIP/FAIMI/EPIMI@MICCAI, том 14242 из Lecture Notes in Computer Science, стр. 276-286. Springer, (2023)

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Raghav Bhaskar

Raghav Aras

Divya Deepak Mehta

Genome-wide association study to search for SNPs affecting gene expression in a general population. TU München, (2009)

Anjula Mehta

Suryakant Kalidas Mehta

 

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M-net: A Convolutional Neural Network for deep brain structure segmentation., и . ISBI, стр. 437-440. IEEE, (2017)Cohort Bias Adaptation in Aggregated Datasets for Lesion Segmentation., , , , , , и . DART/FAIR@MICCAI, том 12968 из Lecture Notes in Computer Science, стр. 101-111. Springer, (2021)Information Gain Sampling for Active Learning in Medical Image Classification., , , и . UNSURE@MICCAI, том 13563 из Lecture Notes in Computer Science, стр. 135-145. Springer, (2022)Improving Image-Based Precision Medicine with Uncertainty-Aware Causal Models., , , , , и . MICCAI (5), том 14224 из Lecture Notes in Computer Science, стр. 472-481. Springer, (2023)To Learn or Not to Learn Features for Deformable Registration?, , и . CoRR, (2017)Improving Pathological Structure Segmentation via Transfer Learning Across Diseases., , , , , , и . DART/MIL3ID@MICCAI, том 11795 из Lecture Notes in Computer Science, стр. 90-98. Springer, (2019)To Learn or Not to Learn Features for Deformable Registration?, , и . MLCN/DLF/iMIMIC@MICCAI, том 11038 из Lecture Notes in Computer Science, стр. 52-60. Springer, (2018)Debiasing Counterfactuals in the Presence of Spurious Correlations., , , , , , и . CLIP/FAIMI/EPIMI@MICCAI, том 14242 из Lecture Notes in Computer Science, стр. 276-286. Springer, (2023)3D U-Net for Brain Tumour Segmentation., и . BrainLes@MICCAI (2), том 11384 из Lecture Notes in Computer Science, стр. 254-266. Springer, (2018)Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis., , и . MIDL, том 227 из Proceedings of Machine Learning Research, стр. 1453-1492. PMLR, (2023)