LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation | Paper Citation Record

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This paper cites Retinal fundus images for glaucoma analysis: the riga dataset.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Retinal fundus images for glaucoma analysis: the riga dataset

Reference 1

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This paper cites Invariant Risk Minimization.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Invariant Risk Minimization

Reference 2

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This paper cites Dropout: Explicit forms and capacity control.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Dropout: Explicit forms and capacity control

Reference 3

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This paper cites P., Cohen-Adad, J., and Hamarneh, G.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation P., Cohen-Adad, J., and Hamarneh, G

Reference 4

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This paper cites Metareg: Towards domain generalization using meta-regularization.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Metareg: Towards domain generalization using meta-regularization

Reference 5

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LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Unresolved cited work

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This paper cites A., Dogan, U., Lee, G., and Scott, C.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation A., Dogan, U., Lee, G., and Scott, C

Reference 7

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LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Unresolved cited work

Reference 8

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This paper cites Treasure in distribution: a domain randomization based multi-source domain generalization for 2d medical image segmentation.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Treasure in distribution: a domain randomization based multi-source domain generalization for 2d medical image segmentation

Reference 9

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This paper cites Domain generalization via model-agnostic learning of semantic features.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Domain generalization via model-agnostic learning of semantic features

Reference 10

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This paper cites and Mordatch, I.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation and Mordatch, I

Reference 11

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This paper cites Compositional visual generation with energy based models.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Compositional visual generation with energy based models

Reference 12

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This paper cites G., and Shao, L.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation G., and Shao, L

Reference 13

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This paper cites O ., Abdulkadir, A., Marrakchi, Y., B \.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation O ., Abdulkadir, A., Marrakchi, Y., B \

Reference 14

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This paper cites H., Moshayedi, A., Roy, G., Dedieu, J., Petit, S., and Hadj, S.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation H., Moshayedi, A., Roy, G., Dedieu, J., Petit, S., and Hadj, S

Reference 15

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This paper cites Model-agnostic meta-learning for fast adaptation of deep networks.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Model-agnostic meta-learning for fast adaptation of deep networks

Reference 16

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This paper cites Domain-adversarial training of neural networks.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Domain-adversarial training of neural networks

Reference 17

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This paper cites Deep Manifold Traversal: Changing Labels with Convolutional Features.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Deep Manifold Traversal: Changing Labels with Convolutional Features

Reference 18

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This paper cites T., Ligett, K., and Wu, S.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation T., Ligett, K., and Wu, S

Reference 19

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LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Unresolved cited work

Reference 20

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This paper cites Domain composition and attention for unseen-domain generalizable medical image segmentation.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Domain composition and attention for unseen-domain generalizable medical image segmentation

Reference 21

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This paper cites and Liu, M.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation and Liu, M

Reference 22

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LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation and Lopez-Paz, D

Reference 23

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LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation and Raginsky, M

Reference 24

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LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation E., Stork, D

Reference 25

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This paper cites Deep residual learning for image recognition.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Deep residual learning for image recognition

Reference 26

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This paper cites Understanding hessian alignment for domain generalization.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Understanding hessian alignment for domain generalization

Reference 27

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LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Unresolved cited work

Reference 28

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This paper cites and Kovashka, A.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation and Kovashka, A

Reference 29

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This paper cites Domain generalization via multidomain discriminant analysis.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Domain generalization via multidomain discriminant analysis

Reference 30

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This paper cites Domain and content adaptive convolution based multi-source domain generalization for medical image segmentation.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Domain and content adaptive convolution based multi-source domain generalization for medical image segmentation

Reference 31

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This paper cites P., and Huang, D.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation P., and Huang, D

Reference 32

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LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation M., Louizos, C., and Welling, M

Reference 33

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LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation F., Kohl, S

Reference 34

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This paper cites D., Chen, Q., Wei, L., and Su, R.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation D., Chen, Q., Wei, L., and Su, R

Reference 35

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This paper cites Unsupervised domain adaptation in brain lesion segmentation with adversarial networks.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Unsupervised domain adaptation in brain lesion segmentation with adversarial networks

Reference 36

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This paper cites Domain generalization on medical imaging classification using episodic training with task augmentation.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Domain generalization on medical imaging classification using episodic training with task augmentation

Reference 37

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This paper cites Learning to generalize: Meta-learning for domain generalization.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Learning to generalize: Meta-learning for domain generalization

Reference 38

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This paper cites J., Wang, S., and Kot, A.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation J., Wang, S., and Kot, A

Reference 39

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This paper cites Progressive domain expansion network for single domain generalization.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Progressive domain expansion network for single domain generalization

Reference 40

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LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Unresolved cited work

Reference 41

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This paper cites Uncertainty Modeling for Out-of-Distribution Generalization.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Uncertainty Modeling for Out-of-Distribution Generalization

Reference 42

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This paper cites Domain generalization via conditional invariant representations.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Domain generalization via conditional invariant representations

Reference 43

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This paper cites H., Liu, Y.-C., Yeh, Y.-Y., and Wang, Y.-C.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation H., Liu, Y.-C., Yeh, Y.-Y., and Wang, Y.-C

Reference 44

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This paper cites Shape-aware meta-learning for generalizing prostate mri segmentation to unseen domains.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Shape-aware meta-learning for generalizing prostate mri segmentation to unseen domains

Reference 45

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Observation f171a984-274e-4c79-b387-8037bef1ff09 · outbound

This paper cites Feddg: Federated domain generalization on medical image segmentation via episodic learning in continuous frequency space.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Feddg: Federated domain generalization on medical image segmentation via episodic learning in continuous frequency space

Reference 46

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Observation 83f4a5eb-2c71-4c06-914b-bdcf1abc9307 · outbound

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LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Unresolved cited work

Reference 47

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Observation 7854e79e-a7d1-45b8-873e-f2d7a73b273f · outbound

This paper cites Geometric and textural augmentation for domain gap reduction.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Geometric and textural augmentation for domain gap reduction

Reference 48

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Observation ece56519-5f4e-49a9-bb11-56aa805dd964 · outbound

This paper cites Domain generalization using causal matching.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Domain generalization using causal matching

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:25.069501Z

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Observation 407b1f14-7651-4c7f-8eed-8587284b489c · outbound

This paper cites V-net: Fully convolutional neural networks for volumetric medical image segmentation.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation V-net: Fully convolutional neural networks for volumetric medical image segmentation

Reference 50

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This paper cites A., and Doretto, G.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation A., and Doretto, G

Reference 51

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This paper cites Domain generalization via invariant feature representation.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Domain generalization via invariant feature representation

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:24.563365Z

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Observation 6e52387d-ea24-4119-92cd-41f59199c24a · outbound

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LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Unresolved cited work

Reference 53

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Observation 4ea600a8-c314-4808-8d20-5984344e7525 · outbound

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LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Unresolved cited work

Reference 54

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Observation 80820377-757b-4d2e-9cf0-504c44626c1a · outbound

This paper cites I., Fu, H., Breda, J.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation I., Fu, H., Breda, J

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:24.029271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 15c18f60-9f8c-4d1b-ba66-05a4be129002 · outbound

This paper cites Two at once: Enhancing learning and generalization capacities via ibn-net.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Two at once: Enhancing learning and generalization capacities via ibn-net

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:23.881909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 163196e0-129e-4dbe-a38f-ca2f84e3a411 · outbound

This paper cites Global and local texture randomization for synthetic-to-real semantic segmentation.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Global and local texture randomization for synthetic-to-real semantic segmentation

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:23.674432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 21ec4cff-92b5-41c0-9e4f-65a8d61af699 · outbound

This paper cites Domain2vec: Domain embedding for unsupervised domain adaptation.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Domain2vec: Domain embedding for unsupervised domain adaptation

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:23.480052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fa133e5b-c3af-4f26-826e-ad0013fd16ed · outbound

This paper cites Structured domain randomization: Bridging the reality gap by context-aware synthetic data.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Structured domain randomization: Bridging the reality gap by context-aware synthetic data

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:23.275690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2b8bc8a2-9fa2-4ddd-8a0a-19c756282652 · outbound

This paper cites Learning to learn single domain generalization.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Learning to learn single domain generalization

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:23.063048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation eba237dd-c27e-4d1d-9abc-d4b0ecc5db5e · outbound

This paper cites M., Fookes, C., Baktashmotlagh, M., and Sridharan, S.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation M., Fookes, C., Baktashmotlagh, M., and Sridharan, S

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:22.912572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7d4cee39-89af-4d62-b042-6d3d95e94afe · outbound

This paper cites Fishr: Invariant gradient variances for out-of-distribution generalization.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Fishr: Invariant gradient variances for out-of-distribution generalization

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T14:15:14.325835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0dfdfdbe-52e7-4115-b3b6-4a3b43ea9564 · outbound

This paper cites J., and Hassani, H.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation J., and Hassani, H

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:22.802055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3dff93c1-d29a-4baf-9b18-a71d63d27b19 · outbound

This paper cites and Ben-David, S.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation and Ben-David, S

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T14:15:14.488562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 216244d5-4624-4397-aaf7-e767badce5cf · outbound

This paper cites Deep learning in medical image analysis.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Deep learning in medical image analysis

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:22.649973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9b39ce83-e713-4fd8-b553-227457f5893a · outbound

This paper cites Gradient matching for domain generalization.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Gradient matching for domain generalization

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:22.478801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1d62101d-e2d1-4388-bb08-568c5e6765ac · outbound

This paper cites D., Jain, M., and Tabish, A.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation D., Jain, M., and Tabish, A

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:22.267489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 866d55b8-2436-46f4-afee-166e3a42db06 · outbound

This paper cites Frustratingly Simple Domain Generalization via Image Stylization.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Frustratingly Simple Domain Generalization via Image Stylization

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-07T14:15:14.810368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c218c65-1bf5-4831-82e1-e4159cef9857 · outbound

This paper cites and Ermon, S.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation and Ermon, S

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T14:15:14.864636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64d5e43d-b776-40ab-bf6c-19eff44364e5 · outbound

This paper cites and Saenko, K.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation and Saenko, K

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T14:15:14.937020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7402ffcb-9472-4156-bdfd-d38a6e4b678c · outbound

This paper cites Fourier features let networks learn high frequency functions in low dimensional domains.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Fourier features let networks learn high frequency functions in low dimensional domains

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:22.070181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fc7e4b6c-e074-4e57-a006-5f4b38069ade · outbound

This paper cites Cycle consistent twin energy-based models for image-to-image translation.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Cycle consistent twin energy-based models for image-to-image translation

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T14:15:15.087217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7fd0a59-e91d-4da1-b9cb-01555506e866 · outbound

This paper cites Bayesian Pseudo-Coresets via Contrastive Divergence.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Bayesian Pseudo-Coresets via Contrastive Divergence

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T14:15:15.184764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 908ef9bf-b380-48b8-afeb-f8ba563bdf21 · outbound

This paper cites Adapt then unlearn: Exploring parameter space semantics for unlearning in generative adversarial networks.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Adapt then unlearn: Exploring parameter space semantics for unlearning in generative adversarial networks

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:21.884474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e1985f6a-915e-4d72-88df-d6cc6f933d75 · outbound

This paper cites Deep feature interpolation for image content changes.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Deep feature interpolation for image content changes

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:21.715540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cfbe8fa1-7271-4ebd-88d4-d32b7a2b879e · outbound

This paper cites an unresolved cited work.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Unresolved cited work

Reference 76

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:15:21.593202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c3899f3d-8c67-411d-a40c-e8c7b15364df · outbound

This paper cites an unresolved cited work.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Unresolved cited work

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-07T14:15:15.555734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f465553-90a9-40ce-94e0-fcf65893deb3 · outbound

This paper cites Dofe: Domain-oriented feature embedding for generalizable fundus image segmentation on unseen datasets.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Dofe: Domain-oriented feature embedding for generalizable fundus image segmentation on unseen datasets

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:21.475385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b9da81e1-1fe9-4a0a-af71-a97eb822ad9e · outbound

This paper cites an unresolved cited work.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Unresolved cited work

Reference 79

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:15:21.370903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 34d6cd29-0e80-4bd6-b0fb-f83ce475306d · outbound

This paper cites Robust and generalizable visual representation learning via random convolutions.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Robust and generalizable visual representation learning via random convolutions

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:21.203786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4cae590b-280c-45b4-8095-93770fc2acab · outbound

This paper cites Tea: Test-time energy adaptation.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Tea: Test-time energy adaptation

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:20.875556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8d7be927-ea64-447b-9a81-9dca0edeb583 · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation mixup: Beyond Empirical Risk Minimization

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-07T14:15:15.904093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc16dcb0-8ef9-4d2e-a069-0c16b5d4b9ad · outbound

This paper cites How Does Mixup Help With Robustness and Generalization?.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation How Does Mixup Help With Robustness and Generalization?

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-07T14:15:15.978471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 160a3c85-4a78-4d97-a360-cc489ea90977 · outbound

This paper cites J., Roth, H., Myronenko, A., Xu, D., et al.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation J., Roth, H., Myronenko, A., Xu, D., et al

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:20.593866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c00abd2a-d5d9-437c-a471-d6b02a19c3e7 · outbound

This paper cites Deep stable learning for out-of-distribution generalization.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Deep stable learning for out-of-distribution generalization

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:20.308576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d26f2aa3-58a5-4898-9223-9a1a084e255c · outbound

This paper cites Exact feature distribution matching for arbitrary style transfer and domain generalization.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Exact feature distribution matching for arbitrary style transfer and domain generalization

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:20.029701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c700ee31-475f-4697-8d89-3dd538a41a54 · outbound

This paper cites S., Liu, J., Wong, W.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation S., Liu, J., Wong, W

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:19.712824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7cda4111-d2fc-4c0d-a5ce-32d48f9a90e9 · outbound

This paper cites and Chen, C.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation and Chen, C

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:19.456647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fd1434ef-8a06-49d0-add1-6ca2a9d60019 · outbound

This paper cites Deep domain-adversarial image generation for domain generalisation.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Deep domain-adversarial image generation for domain generalisation

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:19.201769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5de44d70-707f-4145-adce-f62349dfc555 · outbound

This paper cites Learning to generate novel domains for domain generalization.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Learning to generate novel domains for domain generalization

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:18.932533Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 90df0b44-bef1-4535-a54c-3937016bad52 · outbound

This paper cites Deep domain-adversarial image generation for domain generalisation.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Deep domain-adversarial image generation for domain generalisation

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:18.704265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c4608b4a-bd8b-460e-9b4d-64f63b326b7f · outbound

This paper cites Domain generalization with mixstyle.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Domain generalization with mixstyle

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:18.545422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8dfc1d04-8330-4e06-aa71-2b4dccf8ddd1 · outbound

This paper cites an unresolved cited work.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Unresolved cited work

Reference 93

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:15:18.394139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 48725cbc-fc83-47b1-90bd-ed015e831493 · outbound

This paper cites C., and Liu, Z.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation C., and Liu, Z

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:18.248581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9819e637-030c-479d-a907-c0ab6d34bc4a · outbound

This paper cites an unresolved cited work.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Unresolved cited work

Reference 95

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:15:18.049487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d75c9d02-3a1d-4cb9-ae72-152fb61c98b9 · outbound

This paper cites Generalizable medical image segmentation via random amplitude mixup and domain specific image restoration.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation Generalizable medical image segmentation via random amplitude mixup and domain specific image restoration

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:17.877494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d624ae3b-61cf-42ac-bdac-e4a90aa1fe97 · outbound

This paper cites A., Volpi, R., Sameki, M., Zhang, J., Sclaroff, S., Murino, V., and Saenko, K.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation A., Volpi, R., Sameki, M., Zhang, J., Sclaroff, S., Murino, V., and Saenko, K

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:15:17.690279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2ff7e515-dfc5-4b05-bab8-56e932bc2216 · outbound

This paper cites write newline.

LangDAug: Langevin Data Augmentation for Multi-Source Domain Generalization in Medical Image Segmentation write newline

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-07T14:15:17.081713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers