Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis | Paper Citation Record

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This paper cites AutoPaint: A Self-Inpainting Method for Unsupervised Anomaly Detection.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis AutoPaint: A Self-Inpainting Method for Unsupervised Anomaly Detection

Reference 1

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This paper cites Sutherland, Michael Arbel, and Arthur Gretton.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Sutherland, Michael Arbel, and Arthur Gretton

Reference 2

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This paper cites In- structpix2pix: Learning to follow image editing instructions.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis In- structpix2pix: Learning to follow image editing instructions

Reference 3

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Observation b4d63442-e3c7-4ad0-afbc-1cdbec431e70 · outbound

This paper cites Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains

Reference 4

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This paper cites Towards robust classification model by coun- terfactual and invariant data generation.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Towards robust classification model by coun- terfactual and invariant data generation

Reference 5

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Observation 28f9456f-f601-45b7-8157-1bc21a4619b2 · outbound

This paper cites Custom-Edit: Text-Guided Image Editing with Customized Diffusion Models.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Custom-Edit: Text-Guided Image Editing with Customized Diffusion Models

Reference 6

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This paper cites Medical diffusion on a budget: Textual Inversion for medical image generation.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Medical diffusion on a budget: Textual Inversion for medical image generation

Reference 7

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This paper cites Semantic image manipulation using scene graphs.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Semantic image manipulation using scene graphs

Reference 8

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Observation f908e21d-80fa-473f-b7cc-ccac16c5453f · outbound

This paper cites Dispositionet: Disentangled pose and identity in semantic image manipulation.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Dispositionet: Disentangled pose and identity in semantic image manipulation

Reference 9

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Observation 0720bca6-709b-47e7-8566-30c3be0cac67 · outbound

This paper cites Scenegenie: Scene graph guided diffusion models for image synthesis.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Scenegenie: Scene graph guided diffusion models for image synthesis

Reference 10

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Observation 4080d841-9cbc-48cb-96c6-720d0467bb3f · outbound

This paper cites An image is worth one word: Personalizing text-to-image generation using textual inversion.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis An image is worth one word: Personalizing text-to-image generation using textual inversion

Reference 11

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Observation c87d5363-c0cb-4683-8506-b4126168b211 · outbound

This paper cites Generative adversarial nets.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Generative adversarial nets

Reference 12

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Observation 50fac90d-8d87-4e93-af6e-e37413e6ecf7 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilib- rium.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Gans trained by a two time-scale update rule converge to a local nash equilib- rium

Reference 13

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This paper cites Denoising dif- fusion probabilistic models.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Denoising dif- fusion probabilistic models

Reference 14

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This paper cites Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison

Reference 15

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Observation eebcaacf-a13b-4c60-9284-058ef7a879b9 · outbound

This paper cites Image-to-image translation with conditional adver- sarial networks.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Image-to-image translation with conditional adver- sarial networks

Reference 16

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Observation 91f7e7fd-60a0-4e32-bea3-ddd86535d6b8 · outbound

This paper cites PRISM: Progressive Restoration for Scene Graph-based Image Manipulation.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis PRISM: Progressive Restoration for Scene Graph-based Image Manipulation

Reference 17

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Observation f8ceee04-7cb0-4255-b792-b6e46801b67b · outbound

This paper cites Conditional gan with an attention-based generator and a 3d discriminator for 3d medical image generation.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Conditional gan with an attention-based generator and a 3d discriminator for 3d medical image generation

Reference 18

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This paper cites Analyzing and improv- ing the image quality of stylegan.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Analyzing and improv- ing the image quality of stylegan

Reference 19

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Observation 6047c4a1-9072-4ca3-9493-0ba265bbab81 · outbound

This paper cites Alias-Free Generative Adversarial Networks.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Alias-Free Generative Adversarial Networks

Reference 20

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Observation 462c3a14-f5af-42c0-9d0e-11055505820c · outbound

This paper cites Denoising diffusion probabilistic models for 3d med- ical image generation.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Denoising diffusion probabilistic models for 3d med- ical image generation

Reference 21

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This paper cites Multi-concept customization of text-to-image diffusion.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Multi-concept customization of text-to-image diffusion

Reference 22

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This paper cites Oasis-3: longitudinal neuroimaging, clin- ical, and cognitive dataset for normal aging and alzheimer disease.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Oasis-3: longitudinal neuroimaging, clin- ical, and cognitive dataset for normal aging and alzheimer disease

Reference 23

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Observation 2b597f60-374e-4e71-b388-30d54322c0e2 · outbound

This paper cites Storygan: A sequential conditional gan for story vi- sualization.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Storygan: A sequential conditional gan for story vi- sualization

Reference 24

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Observation 7e51e46f-88ce-4996-a075-10616f358b6f · outbound

This paper cites EditGAN: High-Precision Semantic Image Editing.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis EditGAN: High-Precision Semantic Image Editing

Reference 25

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This paper cites Physics-Informed Latent Diffusion for Multimodal Brain MRI Synthesis.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Physics-Informed Latent Diffusion for Multimodal Brain MRI Synthesis

Reference 26

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Observation 41aefcb7-46b3-4038-b27e-113cd1d47a7f · outbound

This paper cites Conditional Generative Adversarial Nets.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Conditional Generative Adversarial Nets

Reference 27

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Observation 66a7ee42-a272-4c36-88d0-2fea9f08c46a · outbound

This paper cites Diffusion proba- bilistic models beat gans on medical images.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Diffusion proba- bilistic models beat gans on medical images

Reference 28

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Observation 707523b6-4d05-4c96-a794-d01853b9bab6 · outbound

This paper cites Improved denoising diffusion probabilistic models.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Improved denoising diffusion probabilistic models

Reference 29

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This paper cites Glide: Towards photorealis- tic image generation and editing with text-guided diffusion models.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Glide: Towards photorealis- tic image generation and editing with text-guided diffusion models

Reference 30

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This paper cites SESAME: Semantic Edit- ing of Scenes by Adding, Manipulating or Erasing Objects.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis SESAME: Semantic Edit- ing of Scenes by Adding, Manipulating or Erasing Objects

Reference 31

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Observation aa598786-ef4f-48f9-b48a-b2db5c0d30ff · outbound

This paper cites Semantic image synthesis with spatially-adaptive nor- malization.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Semantic image synthesis with spatially-adaptive nor- malization

Reference 32

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This paper cites Zero-shot image-to-image translation.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Zero-shot image-to-image translation

Reference 33

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Observation 1ec43c80-8e68-4724-bb1d-d5667308af54 · outbound

This paper cites Generating Realistic Brain MRIs via a Conditional Diffusion Probabilistic Model.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Generating Realistic Brain MRIs via a Conditional Diffusion Probabilistic Model

Reference 34

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This paper cites Brain imaging generation with latent diffusion models.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Brain imaging generation with latent diffusion models

Reference 35

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This paper cites Equitable modelling of brain imaging by coun- terfactual augmentation with morphologically constrained 3d deep generative models.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Equitable modelling of brain imaging by coun- terfactual augmentation with morphologically constrained 3d deep generative models

Reference 36

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Observation 7fcf64df-e3f0-45a9-85c4-f55e50756a39 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Learning transferable visual models from natural language supervi- sion

Reference 37

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This paper cites Degenerative adversarial neuroimage nets: generating images that mimic disease progression.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Degenerative adversarial neuroimage nets: generating images that mimic disease progression

Reference 38

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Observation 3feb33ba-2b9c-4f1a-ae34-baab986e9f6b · outbound

This paper cites Degenerative adver- sarial neuroimage nets for brain scan simulations: Applica- tion in ageing and dementia.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Degenerative adver- sarial neuroimage nets for brain scan simulations: Applica- tion in ageing and dementia

Reference 39

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Observation 15112218-a4e8-47d1-8709-172b2e5e3535 · outbound

This paper cites High-resolution image synthesis with latent diffusion models.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis High-resolution image synthesis with latent diffusion models

Reference 40

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This paper cites Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:19:20.581776Z

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Observation 8f9c0d2c-d329-4694-b30d-28524d5065ca · outbound

This paper cites Counterfactual generative networks.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Counterfactual generative networks

Reference 42

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Observation a344a6c3-08c2-4a59-b83d-7c03cb56b9f9 · outbound

This paper cites Laion-5b: An open large-scale dataset for training next generation image-text models.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Laion-5b: An open large-scale dataset for training next generation image-text models

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:19:20.547023Z

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Observation a5a00c6b-1e77-4d3f-a30d-e49332cb054f · outbound

This paper cites Denoising Diffusion Implicit Models.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Denoising Diffusion Implicit Models

Reference 44

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Observation 5f5b4b03-2130-4013-925c-35ec8e357e5f · outbound

This paper cites Image synthesis from reconfig- urable layout and style.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Image synthesis from reconfig- urable layout and style

Reference 45

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Observation 461c3137-ed31-48b1-9242-9992207cf775 · outbound

This paper cites Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Embracing imperfect datasets: A review of deep learning solutions for medical image segmentation

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:19:20.512410Z

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Observation d019d5d3-8e55-4eb0-9559-7b347e8e0d2f · outbound

This paper cites Coun- terfactual explanations without opening the black box: Au- tomated decisions and the gdpr.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Coun- terfactual explanations without opening the black box: Au- tomated decisions and the gdpr

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:19:20.494095Z

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Observation c0c63682-d87b-409d-9e79-7a20db2e646b · outbound

This paper cites High-resolution image syn- thesis and semantic manipulation with conditional gans.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis High-resolution image syn- thesis and semantic manipulation with conditional gans

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:19:20.477021Z

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Observation 3885250d-6710-4b8d-95cb-4853d447c697 · outbound

This paper cites Weiner, Dallas P.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Weiner, Dallas P

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:19:20.459384Z

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Observation 6c097418-a4b6-45de-9dc2-b74d442c5a7b · outbound

This paper cites Tsaftaris.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Tsaftaris

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:19:20.438283Z

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Observation 1ca51506-64b4-476b-afda-04d9081dd214 · outbound

This paper cites Anatomy-aware masking for inpainting in medical imaging.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Anatomy-aware masking for inpainting in medical imaging

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:19:20.418100Z

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Observation 0901b06d-6ded-4bfd-a43e-9bfa900e53e2 · outbound

This paper cites Visage: Video synthesis using action graphs for surgery.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Visage: Video synthesis using action graphs for surgery

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:19:20.395193Z

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Observation 399a0110-446d-49cf-8f4c-81d63975022e · outbound

This paper cites Sadm: Sequence-aware diffusion model for longitudinal medical image generation.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Sadm: Sequence-aware diffusion model for longitudinal medical image generation

Reference 53

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Observation 96f9ca95-69a4-49dd-8319-239a9d4db2f3 · outbound

This paper cites Large-scale robust deep auc maximization: A new surrogate loss and empirical studies on medical image classification.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Large-scale robust deep auc maximization: A new surrogate loss and empirical studies on medical image classification

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:19:20.358278Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4b5d74dd-9c6f-47ef-9698-a97a0fabc932 · outbound

This paper cites Image generation from layout.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Image generation from layout

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:19:20.337774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation da6a482d-4c7c-4b40-8a69-29f91a55d15d · outbound

This paper cites Unpaired image-to-image translation using cycle- consistent adversarial networks.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Unpaired image-to-image translation using cycle- consistent adversarial networks

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T23:19:20.319053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5aa345ba-def2-450c-9dca-6567cf92fad7 · outbound

This paper cites an unresolved cited work.

Latent Drifting in Diffusion Models for Counterfactual Medical Image Synthesis Unresolved cited work

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-10T23:19:19.792988Z

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Unavailable: canonical work link unavailable.

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