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Paper Citation Record · LEDGER

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements

As of 18 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2412.14897.

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

pith.paper-citation-record.v1
2412.14897 v1

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measured 56 of 56 reference resolution

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One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

56 of 56 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 20c1d808-a548-4418-b1e2-6cf2007a9b71 · outbound

This paper cites Anderson.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Anderson

Reference 1

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Observation b17afe63-da7c-4068-9ceb-c84c0260a9f1 · outbound

This paper cites The protein data bank.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements The protein data bank

Reference 2

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Observation ec1e46f7-2e65-4a8d-b2e3-dbb476954222 · outbound

This paper cites Monte Carlo guided Diffusion for Bayesian linear inverse problems.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Monte Carlo guided Diffusion for Bayesian linear inverse problems

Reference 3

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Observation 2a585953-83a1-4c47-8e74-a176b46e0145 · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements ShapeNet: An Information-Rich 3D Model Repository

Reference 4

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Observation 2434f8d8-8822-4730-b448-3596b0a82920 · outbound

This paper cites Improving Diffusion Models for Inverse Problems using Manifold Constraints.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Improving Diffusion Models for Inverse Problems using Manifold Constraints

Reference 5

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Observation bf482c80-0422-45e9-8ce6-a872fb9b95f3 · outbound

This paper cites Diffusion Posterior Sampling for General Noisy Inverse Problems.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Diffusion Posterior Sampling for General Noisy Inverse Problems

Reference 6

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Observation 57dd7506-ac44-41cc-aacf-f233c20a82b1 · outbound

This paper cites On implementing 2D rectangular assignment algorithms.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements On implementing 2D rectangular assignment algorithms

Reference 7

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Observation 5691ee93-0a65-4add-91de-cf74a3119a10 · outbound

This paper cites Diffusion Models Beat GAN s on Image Synthesis.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Diffusion Models Beat GAN s on Image Synthesis

Reference 8

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Source-reported events for the cited work

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Observation bc3fade6-f773-4d01-afdb-dc0c328da104 · outbound

This paper cites Diffusion Posterior Sampling for Linear Inverse Problem Solving: A Filtering Perspective.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Diffusion Posterior Sampling for Linear Inverse Problem Solving: A Filtering Perspective

Reference 9

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Observation c8f3d1b7-c3fb-41ab-b0e6-e5db5c0fc5f1 · outbound

This paper cites Hyperdiffusion: Generating implicit neural fields with weight-space diffusion.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Hyperdiffusion: Generating implicit neural fields with weight-space diffusion

Reference 10

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Observation c765ecd7-3058-4f7b-a548-8ae6489b0449 · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Fast Graph Representation Learning with PyTorch Geometric

Reference 11

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Observation b275530d-c6a1-4254-b508-ad8094dc64d2 · outbound

This paper cites Cryo2structdata: A large labeled cryo-em density map dataset for ai-based modeling of protein structures.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Cryo2structdata: A large labeled cryo-em density map dataset for ai-based modeling of protein structures

Reference 12

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Observation 5dfd7182-2f6e-49db-8882-7f5c62674184 · outbound

This paper cites Diffusion Posterior Sampling is Computationally Intractable.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Diffusion Posterior Sampling is Computationally Intractable

Reference 13

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Observation 57fc2c0b-ba2b-46aa-aaec-9e8203e6eab6 · outbound

This paper cites Classifier-Free Diffusion Guidance , 2022.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Classifier-Free Diffusion Guidance , 2022

Reference 14

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Source-reported events for the cited work

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Observation a5a5de39-5d3a-46ac-9344-9b82ef1e6e77 · outbound

This paper cites Denoising Diffusion Probabilistic Models.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Denoising Diffusion Probabilistic Models

Reference 15

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Observation 6d0e5075-1909-4e43-8fcb-7f264a108f1f · outbound

This paper cites an unresolved cited work.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Unresolved cited work

Reference 16

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Observation 87b25a62-f4a8-402a-9511-ea6775b82300 · outbound

This paper cites Estimation of Non-Normalized Statistical Models by Score Matching.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Estimation of Non-Normalized Statistical Models by Score Matching

Reference 17

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Observation 31483132-1fe1-4fef-a0f7-81c22c4e17b0 · outbound

This paper cites Ingraham, Max Baranov, Zak Costello, Karl W.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Ingraham, Max Baranov, Zak Costello, Karl W

Reference 18

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Observation ea348251-c493-48fa-96f1-0a36dfc7ebc0 · outbound

This paper cites Zero-Shot Text-Guided Object Generation with Dream Fields.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Zero-Shot Text-Guided Object Generation with Dream Fields

Reference 19

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Observation 870b052e-d97b-4b14-b99e-17493227f4f3 · outbound

This paper cites Shap-E: Generating Conditional 3D Implicit Functions.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Shap-E: Generating Conditional 3D Implicit Functions

Reference 20

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Observation 12c594bc-5263-4cf4-a0a0-b2775abd8ef0 · outbound

This paper cites Elucidating the Design Space of Diffusion-Based Generative Models.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Elucidating the Design Space of Diffusion-Based Generative Models

Reference 21

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Observation caacb39b-fb28-4e6c-88de-82aa4a834bab · outbound

This paper cites Analyzing and Improving the Training Dynamics of Diffusion Models , 2024.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Analyzing and Improving the Training Dynamics of Diffusion Models , 2024

Reference 22

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Observation a0417442-dc8d-4bc5-9207-d6f29c34a6b2 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Adam: A Method for Stochastic Optimization

Reference 23

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source=arxiv_source observed=2026-08-11T11:54:07.716594Z digest=sha256:b4cb883928c431839cdff94c9a92dd6178e2270b7fdad7b964f96371af08692d

Observation cd5110fc-cae2-4d19-a7b9-807c58c87cf7 · outbound

This paper cites Latent Space Diffusion Models of Cryo-EM Structures.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Latent Space Diffusion Models of Cryo-EM Structures

Reference 24

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Observation e8c001db-ca46-4a80-b1e1-dd720717c335 · outbound

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Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Unresolved cited work

Reference 25

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Observation 762ee904-3c89-42d0-ab59-bf068a85fd94 · outbound

This paper cites One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimization.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimization

Reference 26

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Observation f79a91af-55a4-47d1-9479-28c3f21788ab · outbound

This paper cites RePaint: Inpainting using Denoising Diffusion Probabilistic Models.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Reference 27

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Source-reported events for the cited work

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Observation cf7691ce-9839-4bad-ab82-ca10bdd92521 · outbound

This paper cites Diffusion Probabilistic Models for 3D Point Cloud Generation.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Diffusion Probabilistic Models for 3D Point Cloud Generation

Reference 28

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Observation 130849fc-5add-400e-8df2-f78929b907cb · outbound

This paper cites Pc2: Projection-conditioned point cloud diffusion for single-image 3d reconstruction.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Pc2: Projection-conditioned point cloud diffusion for single-image 3d reconstruction

Reference 29

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Source-reported events for the cited work

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Observation ced3be58-3da0-4f5f-b851-3104bea9af26 · outbound

This paper cites Srinivasan, Matthew Tancik, Jonathan T.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Srinivasan, Matthew Tancik, Jonathan T

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:54:07.743563Z digest=sha256:4c9535a2fe0be5b267fa0750049cb215d7bf6121a2c561f02dadbcd4f7f445f1

Observation 4e0554bd-94d5-420b-ab69-fe6817e20ca5 · outbound

This paper cites Point-e: A system for generating 3d point clouds from complex prompts, 2022.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Point-e: A system for generating 3d point clouds from complex prompts, 2022

Reference 31

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verified fuzzy
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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-11T11:54:07.746871Z digest=sha256:d9afacab27550ba8a2cf33205ff867f0ac7b9fcfbc5de8ba1c1816cedf8ecdd8

Observation 71b15891-fa69-47cf-963d-cc9c65f2a08f · outbound

This paper cites Pedregosa, G.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Pedregosa, G

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:54:07.750026Z digest=sha256:2f6eb707577a6a20c284e09844acbc5e0417be423e247283d01bd93764ce7ba8

Observation f55cea5e-cc23-4bbf-8477-2de3892444bb · outbound

This paper cites cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination

Reference 33

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T11:54:07.753251Z digest=sha256:e9d93bb7d50ddf53a99e318535594a73e1f99f0264f2dbd3d028f680641c0fa9

Observation cf1e8c7f-3286-4a30-9493-31869036efa5 · outbound

This paper cites RELION: implementation of a Bayesian approach to cryo-EM structure determination.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements RELION: implementation of a Bayesian approach to cryo-EM structure determination

Reference 34

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T11:54:07.756582Z digest=sha256:6250fa594735b574cfb1638c1ccdeb64c0a7a55a4fadafbb28d9ac5485bb4098

Observation 3f4b8c58-63c4-404d-b606-a12db8b73e7c · outbound

This paper cites PyMOL , 2020.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements PyMOL , 2020

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 30404229-0810-4a97-b64d-2dc265077ec3 · outbound

This paper cites Deep Unsupervised Learning using Nonequilibrium Thermodynamics.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Reference 36

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raw_fallback, observed 2026-08-11T11:54:08.541697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T11:54:07.763293Z digest=sha256:e6e3fb26764ffd9f041977610ee066ac0039a8739f181780ea121df4ef3fa071

Observation 7688a223-d567-4d1a-9190-84c7cc88b2e8 · outbound

This paper cites Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency

Reference 37

Resolution
verified fuzzy
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T11:54:07.766886Z digest=sha256:6d66fef76e680b97014930f03f3b538ec5abca44c86a30f6e2c2a5f868a56458

Observation 8441b9f4-e568-40d3-a963-05c73ddb262b · outbound

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

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Generative modeling by estimating gradients of the data distribution

Reference 38

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:54:07.770219Z digest=sha256:647546433aa5ad6c939bf789735aea3d258430495d132dedc9a61a2778ab48b8

Observation df0a899e-1c11-46e6-b808-845718913abb · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Score-Based Generative Modeling through Stochastic Differential Equations

Reference 39

Resolution
verified fuzzy
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2a5d108b-427c-4a8a-b32d-9a9b95417ef0 · outbound

This paper cites Methods for cryo-EM single particle reconstruction of macromolecules having continuous heterogeneity.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Methods for cryo-EM single particle reconstruction of macromolecules having continuous heterogeneity

Reference 40

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T11:54:07.777317Z digest=sha256:45e55d5337d2a6658012581943a11c1fb2caa35a6f6648a0bb2a61916b1f5c66

Observation 811ab158-92d0-4670-81e9-9cad6f821a91 · outbound

This paper cites Trippe, Luhuan Wu, Christian A.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Trippe, Luhuan Wu, Christian A

Reference 41

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T11:54:07.780807Z digest=sha256:ad15c085a98f0e320b897728f2fb95d4257f6fcec9222b933ffdb42fcb3eec64

Observation a94a4919-4218-4202-9371-64da377b790e · outbound

This paper cites Trippe, Jason Yim, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, and Tommi S.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Trippe, Jason Yim, Doug Tischer, David Baker, Tamara Broderick, Regina Barzilay, and Tommi S

Reference 42

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T11:54:07.784753Z digest=sha256:b18b3ea5cecba86f6b7c03ace6d4dc82a70b767d418563a3e93bafb377acef27

Observation 20766408-1a86-4280-86fb-2e2a496ce052 · outbound

This paper cites A correlation-based approach to robust point set registration.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements A correlation-based approach to robust point set registration

Reference 43

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T11:54:07.789017Z digest=sha256:ae328a7adda65023fa5b8512d4c3cfc514d796631e2f86818635294ff5e7b2d4

Observation 0da8b809-3943-4e09-976e-6d6a8683c06a · outbound

This paper cites Lion: Latent point diffusion models for 3d shape generation.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Lion: Latent point diffusion models for 3d shape generation

Reference 44

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T11:54:07.792892Z digest=sha256:d4c33ac27f28fa043a3154aed31605829092b8669c39585d5c68d20de6cb1a64

Observation b7333a44-7b70-49ec-81a2-aff66ae6f577 · outbound

This paper cites A Connection Between Score Matching and Denoising Autoencoders.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements A Connection Between Score Matching and Denoising Autoencoders

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-11T11:54:07.796788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:54:07.796788Z digest=sha256:747adeed03066d594f388d84abf2e7e0e10619155c5c1d3ddd0885ba15750bd4

Observation 4ed41866-b4a4-4b0e-8cb5-36dcb00e696a · outbound

This paper cites Diffmodeler: large macromolecular structure modeling for cryo-em maps using a diffusion model.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Diffmodeler: large macromolecular structure modeling for cryo-em maps using a diffusion model

Reference 46

Resolution
verified exact
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T11:54:07.800416Z digest=sha256:93c8954f9efc884dfc9b211860ea08c3fa5c5812c665f70db35a58ef3d34c0a7

Observation fb97fa9f-30ba-4b6f-82ad-1f1c1e98fdab · outbound

This paper cites Bayesian Diffusion Models for 3D Shape Reconstruction.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Bayesian Diffusion Models for 3D Shape Reconstruction

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T11:54:08.435282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T11:54:07.804165Z digest=sha256:a4bcda24e073d66f51027bccfd41d6e149d00426ec28b1c77751f248b4a4fcdc

Observation 3ca82984-d1aa-43a6-8969-097c39fe465d · outbound

This paper cites Pointflow: 3d point cloud generation with continuous normalizing flows.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Pointflow: 3d point cloud generation with continuous normalizing flows

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T11:54:08.423446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T11:54:07.807833Z digest=sha256:26910a2305941c2e1e58a12927a41628da70b95dc75e52b241ffefeaad21fa38

Observation b407a220-194c-4bce-9057-22f3a07b6752 · outbound

This paper cites Robust single-particle cryo-em image denoising and restoration.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Robust single-particle cryo-em image denoising and restoration

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-11T11:54:07.811455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:54:07.811455Z digest=sha256:1089868bab6d2f58255c6fa229050b073b308f1c0a7f84e3bc78f06dd5922ce4

Observation 15334393-91b4-483c-84a7-6b6ec2fa6a58 · outbound

This paper cites Zhong, Tristan Bepler, Bonnie Berger, and Joseph H.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Zhong, Tristan Bepler, Bonnie Berger, and Joseph H

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-11T11:54:07.815486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:54:07.815486Z digest=sha256:d04e3404af71b1864a0dfffa334e38757e826486c9af398bdf0a8ab416420424

Observation 17aa2722-de14-46c8-b743-9aa14bb1dece · outbound

This paper cites Zhong, Adam Lerer, Joseph H.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Zhong, Adam Lerer, Joseph H

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T11:54:08.410235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T11:54:07.819105Z digest=sha256:31500f8a0d9d9ef8b94cfc1e3724acf1563ada1226f0a52d6b9f90be8e21ca2f

Observation 38959fc1-3694-4352-9e24-5aac7962f109 · outbound

This paper cites 3d shape generation and completion through point-voxel diffusion.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements 3d shape generation and completion through point-voxel diffusion

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T11:54:08.397200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T11:54:07.822565Z digest=sha256:b1773403bdbcfae46a5749814ddd93724655a9cced48b5933d11932b4a522771

Observation bfc50dcb-92e8-41d5-942b-fb9e000d594f · outbound

This paper cites write newline.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements write newline

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-11T11:54:07.826085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:54:07.826085Z digest=sha256:a7e02541dea7a4b8b9c1fb31f03f74aad19fa45cdc744e8080f943dc2978a4ef

Observation a22ffafa-7fda-4589-966c-fc0d2d7f4f3f · outbound

This paper cites @esa (Ref.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements @esa (Ref

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-11T11:54:07.830368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:54:07.830368Z digest=sha256:c6e0c24a644afc6ffecde48154bd6c2367ff8c391670d4a8483668f6be5ec0b8

Observation ab2dec7c-1a96-4617-8b07-a3fbbc726c22 · outbound

This paper cites an unresolved cited work.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements Unresolved cited work

Reference 55

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:54:07.834462Z digest=sha256:65d60588aff6f978aac129ce576ee09918b633ca469e8ca5197413002d5ca83a

Observation b5330c65-bf18-4b2d-a669-4fdda9020cf3 · outbound

This paper cites ** ! Emergency stop.

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements ** ! Emergency stop

Reference 56

Resolution
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-11T11:54:07.838263Z digest=sha256:e9bb5c920eb201dcc42341a013a49cfaaa14ada518b59cdee6ccaba46c84f0bc

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