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Paper Citation Record · LEDGER

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization

As of 14 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2607.10777.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.10777 v1

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measured 60 of 60 reference resolution

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60 of 60 outbound references displayed

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Outbound references

Observation 498868e0-2a8c-4092-9422-2e5ad74d7166 · outbound

This paper cites Distribution matching losses can hallucinate features in medical image translation.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Distribution matching losses can hallucinate features in medical image translation

Reference 1

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Observation ffd920f0-362a-46c7-bbf6-c70d3d18c68b · outbound

This paper cites URLhttps://doi.org/10.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization URLhttps://doi.org/10

Reference 2

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Observation 3a052fbf-09b8-44c1-b285-17c805816b27 · outbound

This paper cites Association of biomarker-based artificial intelligence with risk of racial bias in retinal images.JAMA ophthalmology, 141(6):543–552, 2023.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Association of biomarker-based artificial intelligence with risk of racial bias in retinal images.JAMA ophthalmology, 141(6):543–552, 2023

Reference 3

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Observation bb775fab-0a99-4945-b75c-e517228f4a93 · outbound

This paper cites Arcface: Additive angular margin loss for deep face recognition.IEEE Trans.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Arcface: Additive angular margin loss for deep face recognition.IEEE Trans

Reference 4

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Observation 12ef96f1-01ab-4846-90ad-e820dfeb9a86 · outbound

This paper cites An image is worth 16x16 words: Trans- formers for image recognition at scale.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization An image is worth 16x16 words: Trans- formers for image recognition at scale

Reference 5

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Observation e980b187-ef15-4edf-9d14-1e511b5140fe · outbound

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RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Unresolved cited work

Reference 6

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Observation 282f8f52-5a19-499b-ac27-896486772aa5 · outbound

This paper cites Tsaftaris, and Timothy M.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Tsaftaris, and Timothy M

Reference 7

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Observation beda79e4-f2da-4fd9-99a4-6b2b943c4c92 · outbound

This paper cites Wich- mann, and Wieland Brendel.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Wich- mann, and Wieland Brendel

Reference 8

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This paper cites URLhttps://openreview.net/forum?id= Bygh9j09KX.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization URLhttps://openreview.net/forum?id= Bygh9j09KX

Reference 9

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This paper cites Ai recognition of patient race in medical imaging: a modelling study.The Lancet Digital Health, 4(6):e406–e414, 2022.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Ai recognition of patient race in medical imaging: a modelling study.The Lancet Digital Health, 4(6):e406–e414, 2022

Reference 10

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Observation 33d11cc9-4d89-4a73-9265-33861c4228f0 · outbound

This paper cites Algorith- mic encoding of protected characteristics in chest x-ray disease detection models.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Algorith- mic encoding of protected characteristics in chest x-ray disease detection models

Reference 11

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Observation 0d4424a1-d9c1-4af3-ab42-2e37423a8bf3 · outbound

This paper cites In search of lost domain generalization.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization In search of lost domain generalization

Reference 12

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This paper cites Equality of opportunity in super- vised learning.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Equality of opportunity in super- vised learning

Reference 14

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RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Unresolved cited work

Reference 15

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This paper cites Mambavision: A hybrid mamba-transformer vision backbone.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Mambavision: A hybrid mamba-transformer vision backbone

Reference 16

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Observation 1bc7bdd3-464b-497c-81e9-5faf3b609849 · outbound

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Reference 17

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Observation fb50428c-cfa7-4895-88d8-d31860f28f90 · outbound

This paper cites Deep residual learning for image recognition.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Deep residual learning for image recognition

Reference 18

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Observation 2df6674c-9d7e-4cf6-9c02-e9967727f700 · outbound

This paper cites Weinberger.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Weinberger

Reference 19

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This paper cites doi: 10.1109/CVPR.2017.243.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization doi: 10.1109/CVPR.2017.243

Reference 20

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Observation 9b2a92ec-5f9b-49a2-acbd-7557d6088a2a · outbound

This paper cites Re- visiting masked image modeling with standardized color space for domain generalized fundus photography classification.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Re- visiting masked image modeling with standardized color space for domain generalized fundus photography classification

Reference 21

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Observation b8c178dd-8c16-4304-b4a9-0d80c6ca733b · outbound

This paper cites Kevin Zhou, and Xiaoxiao Li.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Kevin Zhou, and Xiaoxiao Li

Reference 22

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Observation eb61dcae-c5e5-4a9f-86d1-e8cbbe6062f7 · outbound

This paper cites PRISM: High-Resolution & Precise Counterfactual Medical Image Generation using Language-guided Stable Diffusion.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization PRISM: High-Resolution & Precise Counterfactual Medical Image Generation using Language-guided Stable Diffusion

Reference 23

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Observation 05799642-43c0-47d1-8412-e5953f067611 · outbound

This paper cites Kusner, Joshua R.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Kusner, Joshua R

Reference 24

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Observation a018ecda-e407-4bda-8fb0-c71649fe9595 · outbound

This paper cites Let samples speak: Mitigating spurious correlation by exploiting the clusterness of samples.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Let samples speak: Mitigating spurious correlation by exploiting the clusterness of samples

Reference 25

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This paper cites Un- certainty modeling for out-of-distribution generalization.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Un- certainty modeling for out-of-distribution generalization

Reference 26

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RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization URLhttps://openreview.net/forum?id= 6HN7LHyzGgC

Reference 27

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RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Incomplete modality disentangled representa- tion for ophthalmic disease grading and diagnosis

Reference 28

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This paper cites Sphereface revived: Unifying hyperspherical face recognition.IEEE Trans.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Sphereface revived: Unifying hyperspherical face recognition.IEEE Trans

Reference 29

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RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Swin transformer: Hierarchical vision transformer using shifted windows

Reference 30

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RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization URLhttps://doi.org/10

Reference 31

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RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization A convnet for the 2020s

Reference 32

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RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Fairvision: Equitable deep learning for eye disease screening via fair identity scaling, 2024

Reference 33

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RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Fairclip: Harnessing fairness in vision-language learning

Reference 34

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RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Shufflenet V2: prac- tical guidelines for efficient CNN architecture design

Reference 35

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RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization URLhttps://doi.org/10.1007/ 978-3-030-01264-9_8

Reference 36

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RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Hyperspherical prototype net- works

Reference 37

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Observation a129940e-1193-4515-99c3-748d6a235d93 · outbound

This paper cites Slicing through bias: Explaining performance gaps in medical image analysis using slice discovery meth- ods.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Slicing through bias: Explaining performance gaps in medical image analysis using slice discovery meth- ods

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Observation 94e5bdc8-dde7-486e-ba02-55d4e919b4ed · outbound

This paper cites Prevalence of Neural Collapse during the terminal phase of deep learning training.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Prevalence of Neural Collapse during the terminal phase of deep learning training

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Observation 1dfa9a9e-604b-4eb0-98be-fb86793a76d5 · outbound

This paper cites Girshick, Kaiming He, and Piotr Dollár.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Girshick, Kaiming He, and Piotr Dollár

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Observation 930cc8f6-3697-4734-8c83-fcc9ab9fed49 · outbound

This paper cites Machine learning derived retinal pigment score from ophthalmic imaging shows ethnicity is not biology.Nature communications, 16(1):60, 2025.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Machine learning derived retinal pigment score from ophthalmic imaging shows ethnicity is not biology.Nature communications, 16(1):60, 2025

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Observation d6100e28-8939-441f-953f-0309c81a8f97 · outbound

This paper cites Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization

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Observation 084066c6-5b4b-4017-a63b-d5415ac39185 · outbound

This paper cites The precision-recall plot is more informative than the roc plot when evaluating binary classifiers on imbalanced datasets.PloS one, 10 (3):e0118432, 2015.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization The precision-recall plot is more informative than the roc plot when evaluating binary classifiers on imbalanced datasets.PloS one, 10 (3):e0118432, 2015

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Observation 8c7df826-9170-47fc-b637-2a25c4c557b9 · outbound

This paper cites vmfcoop: Towards equilibrium on a unified hyperspherical manifold for prompt- ing biomedical vlms.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization vmfcoop: Towards equilibrium on a unified hyperspherical manifold for prompt- ing biomedical vlms

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Observation ba7dfe47-bad4-4e29-8f16-75b65beb60a6 · outbound

This paper cites A 3x3 isotropic gradient operator for image process- ing.a talk at the Stanford Artificial Project in, 1968:271–272, 1968.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization A 3x3 isotropic gradient operator for image process- ing.a talk at the Stanford Artificial Project in, 1968:271–272, 1968

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Observation 774c42de-bc8d-4659-8457-5c058c35c175 · outbound

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RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Unresolved cited work

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Observation e1088c15-c59c-488b-bf6e-65e22fd66d12 · outbound

This paper cites Fairdomain: Achiev- ing fairness in cross-domain medical image segmentation and classification.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Fairdomain: Achiev- ing fairness in cross-domain medical image segmentation and classification

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This paper cites Bovik, and Yinxiao Li.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Bovik, and Yinxiao Li

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Observation ae91d32e-7711-485e-92aa-9b7a7446dccb · outbound

This paper cites Gilligan-Lee.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Gilligan-Lee

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This paper cites URLhttps://doi.org/10.1038/ s42256-023-00611-x.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization URLhttps://doi.org/10.1038/ s42256-023-00611-x

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Observation 1d9b31ee-0db3-46d8-a925-73d486b624f7 · outbound

This paper cites Cosface: Large margin cosine loss for deep face recog- nition.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Cosface: Large margin cosine loss for deep face recog- nition

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Observation b2972a14-850e-407f-bf18-b1fe4515e72a · outbound

This paper cites Navigate beyond shortcuts: Debiased learning through the lens of neural collapse.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Navigate beyond shortcuts: Debiased learning through the lens of neural collapse

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Observation 714cd4e6-bd51-4c86-9c64-2b6bd475346c · outbound

This paper cites Fast diffusion-based counterfactuals for shortcut removal and generation.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Fast diffusion-based counterfactuals for shortcut removal and generation

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Observation 7a28a17a-9397-4d24-b085-33d28fab7d62 · outbound

This paper cites Generalizing to unseen domains in diabetic retinopa- thy with disentangled representations.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Generalizing to unseen domains in diabetic retinopa- thy with disentangled representations

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Observation 26b1af6a-e3bc-42df-9c13-30cc58d5df62 · outbound

This paper cites URLhttps://doi.org/10.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization URLhttps://doi.org/10

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Observation 1a9d4bdb-c3e3-4999-8e99-24f84dd22282 · outbound

This paper cites The limits of fair medical imaging ai in real-world generalization.Nature medicine, 30 (10):2838–2848, 2024.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization The limits of fair medical imaging ai in real-world generalization.Nature medicine, 30 (10):2838–2848, 2024

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This paper cites Mitigating unwanted bi- ases with adversarial learning.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Mitigating unwanted bi- ases with adversarial learning

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This paper cites doi: 10.1145/3278721.3278779.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization doi: 10.1145/3278721.3278779

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Observation 1dd21155-c450-47e9-b44a-d1f761c2b726 · outbound

This paper cites Exact feature distri- bution matching for arbitrary style transfer and domain generalization.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Exact feature distri- bution matching for arbitrary style transfer and domain generalization

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Observation 7bc258db-bd45-4fa4-84a8-bd969ad2b969 · outbound

This paper cites Prototype correlation matching and class- relation reasoning for few-shot medi- cal image segmentation.IEEE Trans.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Prototype correlation matching and class- relation reasoning for few-shot medi- cal image segmentation.IEEE Trans

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Observation 5a6f660d-3f09-495f-ba7e-b20a9e1e4f62 · outbound

This paper cites Discover and mit- igate multiple biased subgroups in image classifiers.

RED-Sphere: Hyperspherical Residual Edge Debiasing for Cross-Population Fundus Disease Domain Generalization Discover and mit- igate multiple biased subgroups in image classifiers

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