Paper Citation Record · LEDGER

Diffusion Models for Computational Neuroimaging: A Survey

As of 17 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2502.06552.

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

pith.paper-citation-record.v1
2502.06552 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:06:47.632059Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

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verified fuzzy23
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5bce893e-5da7-4db5-aa66-b0092edd7139 · outbound

This paper cites Federated learning for pri- vacy preservation in smart healthcare systems: A compre- hensive survey.

Diffusion Models for Computational Neuroimaging: A Survey Federated learning for pri- vacy preservation in smart healthcare systems: A compre- hensive survey

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:48.139426Z

Source-reported events for the cited work

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Observation fb1ff092-abb3-437f-b569-48204b8722f9 · outbound

This paper cites Deep learning in neuroimaging data analysis: applications, challenges, and solutions.

Diffusion Models for Computational Neuroimaging: A Survey Deep learning in neuroimaging data analysis: applications, challenges, and solutions

Reference 4

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Observation 31d78df6-9fab-4a3f-9398-93945033df05 · outbound

This paper cites Seeing beyond the brain: Conditional diffusion model with sparse masked modeling for vision decoding.

Diffusion Models for Computational Neuroimaging: A Survey Seeing beyond the brain: Conditional diffusion model with sparse masked modeling for vision decoding

Reference 5

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Observation 9431aabb-2c9d-40f4-ba51-2ffabfb72db8 · outbound

This paper cites Deconstructing Denoising Diffusion Models for Self-Supervised Learning.

Diffusion Models for Computational Neuroimaging: A Survey Deconstructing Denoising Diffusion Models for Self-Supervised Learning

Reference 6

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Observation 07bc4a78-9dba-4382-a9a7-5fe436e7f443 · outbound

This paper cites Contrastive diffusion model with auxiliary guidance for coarse-to-fine pet reconstruction.

Diffusion Models for Computational Neuroimaging: A Survey Contrastive diffusion model with auxiliary guidance for coarse-to-fine pet reconstruction

Reference 9

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Source-reported events for the cited work

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Observation 85bd74df-d398-4e5c-8dfb-950bdbec9c33 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Diffusion Models for Computational Neuroimaging: A Survey Classifier-Free Diffusion Guidance

Reference 10

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Source-reported events for the cited work

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Observation eb362942-56f8-4b8d-bb4d-cd80d31c7db6 · outbound

This paper cites Denoising diffusion probabilistic models.

Diffusion Models for Computational Neuroimaging: A Survey Denoising diffusion probabilistic models

Reference 11

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Observation e683e1d0-dfe2-4f46-81d3-e726ca8f1065 · outbound

This paper cites Adaptive latent diffusion model for 3d medical image to image translation: Multi-modal magnetic resonance imag- ing study.

Diffusion Models for Computational Neuroimaging: A Survey Adaptive latent diffusion model for 3d medical image to image translation: Multi-modal magnetic resonance imag- ing study

Reference 13

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Observation 84886d85-0081-4c53-bd4d-797f27367d66 · outbound

This paper cites Reverse the auditory processing pathway: Coarse-to-fine audio reconstruction from fMRI.

Diffusion Models for Computational Neuroimaging: A Survey Reverse the auditory processing pathway: Coarse-to-fine audio reconstruction from fMRI

Reference 14

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Observation 318380f9-786a-400e-b87e-d87785270dc7 · outbound

This paper cites Segment anything in medi- cal images.

Diffusion Models for Computational Neuroimaging: A Survey Segment anything in medi- cal images

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:48.023709Z

Source-reported events for the cited work

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Observation 835a5cd9-248b-4b1b-8ab6-20ce0c776b2d · outbound

This paper cites Disc-diff: Disentangled conditional diffusion model for multi-contrast mri super-resolution.

Diffusion Models for Computational Neuroimaging: A Survey Disc-diff: Disentangled conditional diffusion model for multi-contrast mri super-resolution

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:48.011143Z

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 909449ee-257a-4154-b534-0041cfeedb46 · outbound

This paper cites Multi-modal modality- masked diffusion network for brain mri synthesis with ran- dom modality missing.

Diffusion Models for Computational Neuroimaging: A Survey Multi-modal modality- masked diffusion network for brain mri synthesis with ran- dom modality missing

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:47.997333Z

Source-reported events for the cited work

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Observation ab250817-b210-42f4-a04f-99e641b1bb92 · outbound

This paper cites Scalable diffusion models with transformers.

Diffusion Models for Computational Neuroimaging: A Survey Scalable diffusion models with transformers

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:47.985393Z

Source-reported events for the cited work

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Observation adbeaa60-01fd-465d-922b-0e6490f937bb · outbound

This paper cites Generating realistic brain mris via a conditional diffusion probabilistic model.

Diffusion Models for Computational Neuroimaging: A Survey Generating realistic brain mris via a conditional diffusion probabilistic model

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:47.972527Z

Source-reported events for the cited work

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Observation 72827a97-3e9e-4cce-94ce-bc5147f1c92e · outbound

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

Diffusion Models for Computational Neuroimaging: A Survey High-resolution image synthesis with latent diffusion models

Reference 20

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Observation a504fe54-2ba4-4fef-bf2e-a4267a824f86 · outbound

This paper cites Generative modeling by estimating gradients of the data distribution.

Diffusion Models for Computational Neuroimaging: A Survey Generative modeling by estimating gradients of the data distribution

Reference 21

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Source-reported events for the cited work

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Observation e428a01e-eb5a-4b53-aa97-030cadd21bfe · outbound

This paper cites Solving inverse problems in medical imaging with score-based generative models.

Diffusion Models for Computational Neuroimaging: A Survey Solving inverse problems in medical imaging with score-based generative models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:47.949667Z

Source-reported events for the cited work

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Observation 656b8f57-582e-48b1-b837-1c0d4f406d28 · outbound

This paper cites Dual Diffusion Implicit Bridges for Image-to-Image Translation.

Diffusion Models for Computational Neuroimaging: A Survey Dual Diffusion Implicit Bridges for Image-to-Image Translation

Reference 23

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Source-reported events for the cited work

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Observation 75ebaede-b0af-4fe4-a7b2-b8b44f8e7581 · outbound

This paper cites High-resolution image reconstruction with latent diffusion models from human brain activity.

Diffusion Models for Computational Neuroimaging: A Survey High-resolution image reconstruction with latent diffusion models from human brain activity

Reference 24

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Source-reported events for the cited work

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Observation 83ca2af4-5432-422d-aa31-15e204db9aab · outbound

This paper cites Self-supervised learning of brain dy- namics from broad neuroimaging data.Advances in neural information processing systems, 35:21255–21269,.

Diffusion Models for Computational Neuroimaging: A Survey Self-supervised learning of brain dy- namics from broad neuroimaging data.Advances in neural information processing systems, 35:21255–21269,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:47.932068Z

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Observation ca2bf34f-e123-4c37-9f3b-9628c4d7c1db · outbound

This paper cites Wkgm: weighted k-space generative model for parallel imaging reconstruc- tion.

Diffusion Models for Computational Neuroimaging: A Survey Wkgm: weighted k-space generative model for parallel imaging reconstruc- tion

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:47.922222Z

Source-reported events for the cited work

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Observation ca078abc-0d12-498f-ba12-a0f8a8b50692 · outbound

This paper cites Inversesr: 3d brain mri super-resolution using a latent diffusion model.

Diffusion Models for Computational Neuroimaging: A Survey Inversesr: 3d brain mri super-resolution using a latent diffusion model

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:47.912600Z

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 49a6a85b-4179-4f4e-ba34-53ab67c2cc6d · outbound

This paper cites Medsegdiff: Medical image segmentation with diffusion probabilistic model.

Diffusion Models for Computational Neuroimaging: A Survey Medsegdiff: Medical image segmentation with diffusion probabilistic model

Reference 28

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Source-reported events for the cited work

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Observation e3f94f2e-10dc-4ec9-9f8c-9cc65b17774a · outbound

This paper cites Diffusion model as representation learner.

Diffusion Models for Computational Neuroimaging: A Survey Diffusion model as representation learner

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:47.891340Z

Source-reported events for the cited work

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Observation cb6838ef-7d46-4d36-b069-3e1efec1b3e6 · outbound

This paper cites Diffusion-ts: Interpretable diffusion for general time series generation.

Diffusion Models for Computational Neuroimaging: A Survey Diffusion-ts: Interpretable diffusion for general time series generation

Reference 30

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Source-reported events for the cited work

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Observation f44570b7-d088-4f3f-acf6-f53d3a2c1625 · outbound

This paper cites Diffusion transformer-augmented fmri func- tional connectivity for enhanced autism spectrum disorder diagnosis.

Diffusion Models for Computational Neuroimaging: A Survey Diffusion transformer-augmented fmri func- tional connectivity for enhanced autism spectrum disorder diagnosis

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:47.869365Z

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 47cee92b-6bee-4a9a-bc53-ce7f95bfe7a7 · outbound

This paper cites Emerging Synergies in Causality and Deep Generative Models: A Survey.

Diffusion Models for Computational Neuroimaging: A Survey Emerging Synergies in Causality and Deep Generative Models: A Survey

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-08-08T15:06:47.741234Z

Source-reported events for the cited work

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Observation 48882516-718f-4bef-8540-957c481135d8 · outbound

This paper cites Brainnetdiff: Gen- erative ai empowers brain network construction via multi- modal diffusion.

Diffusion Models for Computational Neuroimaging: A Survey Brainnetdiff: Gen- erative ai empowers brain network construction via multi- modal diffusion

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:47.857475Z

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 4b7b1a73-7930-4779-b60c-ecf6c7145b01 · outbound

This paper cites A new brain network construction paradigm for brain disorder via diffusion-based graph contrastive learning.

Diffusion Models for Computational Neuroimaging: A Survey A new brain network construction paradigm for brain disorder via diffusion-based graph contrastive learning

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:47.845852Z

Source-reported events for the cited work

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Observation 495b6964-1dc0-4c7f-86e0-60192824a63c · outbound

This paper cites Cola-diff: Conditional latent diffu- sion model for multi-modal mri synthesis.

Diffusion Models for Computational Neuroimaging: A Survey Cola-diff: Conditional latent diffu- sion model for multi-modal mri synthesis

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:48.049352Z

Source-reported events for the cited work

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Observation 8d6127b3-74f3-4481-9269-cb249f11493f · outbound

This paper cites Federated learning vul- nerabilities: Privacy attacks with denoising diffusion prob- abilistic models.

Diffusion Models for Computational Neuroimaging: A Survey Federated learning vul- nerabilities: Privacy attacks with denoising diffusion prob- abilistic models

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:48.080881Z

Source-reported events for the cited work

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Observation 2295aad9-c4a4-4bcd-863a-0e8a03de756d · outbound

This paper cites Synthetic sleep eeg signal generation using latent diffusion models.

Diffusion Models for Computational Neuroimaging: A Survey Synthetic sleep eeg signal generation using latent diffusion models

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:48.129444Z

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 2796b7a9-94b0-4d74-b104-c729d37884c6 · outbound

This paper cites Diffusion vi- sual counterfactual explanations.

Diffusion Models for Computational Neuroimaging: A Survey Diffusion vi- sual counterfactual explanations

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T15:06:48.119245Z

Source-reported events for the cited work

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Observation 93cdf0ac-11a3-41e0-99ad-90827b95afd5 · outbound

This paper cites Diffusion models beat gans on image synthe- sis.

Diffusion Models for Computational Neuroimaging: A Survey Diffusion models beat gans on image synthe- sis

Reference 2024

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Source-reported events for the cited work

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Observation d8325bc7-ede2-43a4-a109-09143a1be1d4 · outbound

This paper cites Generative AI Enables EEG Super-Resolution via Spatio-Temporal Adaptive Diffusion Learning.

Diffusion Models for Computational Neuroimaging: A Survey Generative AI Enables EEG Super-Resolution via Spatio-Temporal Adaptive Diffusion Learning

Reference 2025

Resolution: verified exact; local_arxiv, observed 2026-08-08T15:06:47.786977Z

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.

Pith citing papers

No inbound Pith citation observations are available.