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Paper Citation Record · LEDGER

Generative modeling of protein ensembles guided by crystallographic electron densities

As of 20 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 3 inbound Pith citation observations for arXiv:2412.13223.

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

pith.paper-citation-record.v1
2412.13223 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:12:38.245871Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T21:49:07.881151Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T14:27:24.132073Z

Reference resolution

17 of 17 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f7d4442f-d72a-4540-a689-f0b0bacadf86 · outbound

This paper cites Se(3)-stochastic flow matching for protein backbone generation.

Generative modeling of protein ensembles guided by crystallographic electron densities Se(3)-stochastic flow matching for protein backbone generation

Reference 1

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Observation 46adc054-2f6c-4a31-8812-75435a029653 · outbound

This paper cites an unresolved cited work.

Generative modeling of protein ensembles guided by crystallographic electron densities Unresolved cited work

Reference 2

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Observation 51be0949-9229-40db-8f1a-2b2af9ab966b · outbound

This paper cites Diffusion models beat gans on image synthesis.

Generative modeling of protein ensembles guided by crystallographic electron densities Diffusion models beat gans on image synthesis

Reference 3

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Observation 5a261f68-b282-4bfd-9240-0104a7de8832 · outbound

This paper cites Modeling with alternate loca- tions in x-ray protein structures.

Generative modeling of protein ensembles guided by crystallographic electron densities Modeling with alternate loca- tions in x-ray protein structures

Reference 4

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Observation c5f56059-e7f0-4b47-a896-1a07ed077efa · outbound

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

Generative modeling of protein ensembles guided by crystallographic electron densities Ingraham, Max Baranov, Zak Costello, Karl W

Reference 5

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Observation 681a751f-1cbb-4351-be47-b173cf9a038b · outbound

This paper cites Alphafold meets flow matching for generating protein ensembles.

Generative modeling of protein ensembles guided by crystallographic electron densities Alphafold meets flow matching for generating protein ensembles

Reference 6

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Observation a3eaa7a4-31b7-435f-a979-d734dedecd78 · outbound

This paper cites Therese Lang, James M.

Generative modeling of protein ensembles guided by crystallographic electron densities Therese Lang, James M

Reference 7

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Observation e0e57fe1-cb72-4850-ad47-dc5295fde6b2 · outbound

This paper cites Matching pursuits with time-frequency dictionaries.

Generative modeling of protein ensembles guided by crystallographic electron densities Matching pursuits with time-frequency dictionaries

Reference 8

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Observation 8afd1de1-0c84-44f5-8964-2e0051013488 · outbound

This paper cites Ucsf chimerax: Structure visualization for researchers, educators, and developers.

Generative modeling of protein ensembles guided by crystallographic electron densities Ucsf chimerax: Structure visualization for researchers, educators, and developers

Reference 9

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Observation 35ba6fe2-c758-4443-8f7e-e52ccffdd8c9 · outbound

This paper cites International Tables for Crystallography, Volume C: Mathematical, physical and chemical tables.

Generative modeling of protein ensembles guided by crystallographic electron densities International Tables for Crystallography, Volume C: Mathematical, physical and chemical tables

Reference 10

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Observation c908ccf2-c6c3-4752-af62-de6b0aaca56d · outbound

This paper cites Rosenberg, Sanketh Vedula, Alex M.

Generative modeling of protein ensembles guided by crystallographic electron densities Rosenberg, Sanketh Vedula, Alex M

Reference 11

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Observation 1ce3d01c-7c2a-4e38-b522-ad7f1bd3d110 · outbound

This paper cites A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions.

Generative modeling of protein ensembles guided by crystallographic electron densities A smoothed backbone-dependent rotamer library for proteins derived from adaptive kernel density estimates and regressions

Reference 12

Resolution
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Source-reported events for the cited work

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Observation 5c2452ec-5938-44ae-9087-f3d697525ef1 · outbound

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

Generative modeling of protein ensembles guided by crystallographic electron densities Generative modeling by estimating gradients of the data distribution

Reference 13

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Source-reported events for the cited work

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Observation eb396972-d2ea-4e91-82d5-51fff25d736a · outbound

This paper cites Partially collapsed gibbs samplers: Theory and methods.

Generative modeling of protein ensembles guided by crystallographic electron densities Partially collapsed gibbs samplers: Theory and methods

Reference 14

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Source-reported events for the cited work

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Observation 9ee598de-efa4-4d8a-bc2a-e35ebcd97229 · outbound

This paper cites Wankowicz, Ashraya Ravikumar, Shivani Sharma, Blake T.

Generative modeling of protein ensembles guided by crystallographic electron densities Wankowicz, Ashraya Ravikumar, Shivani Sharma, Blake T

Reference 15

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Source-reported events for the cited work

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Observation 584d15ba-fa99-4fca-8193-b718e860e355 · outbound

This paper cites Bron- stein, and Renana Gershoni-Poranne.

Generative modeling of protein ensembles guided by crystallographic electron densities Bron- stein, and Renana Gershoni-Poranne

Reference 16

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Source-reported events for the cited work

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Observation be63094d-b7ec-4d8b-97e6-b389cecb56ba · outbound

This paper cites Predicting equilibrium distributions for molecular systems with deep learning.

Generative modeling of protein ensembles guided by crystallographic electron densities Predicting equilibrium distributions for molecular systems with deep learning

Reference 17

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Pith citing papers

Observation a908d989-484f-4760-a7eb-cd81ce678fc8 · inbound

Inverse problems with experiment-guided AlphaFold cites this paper.

Inverse problems with experiment-guided AlphaFold Generative modeling of protein ensembles guided by crystallographic electron densities

Reference 33

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Observation 0dcd2b8b-3f9e-4bc6-bca1-9ade4825442f · inbound

Dual Ascent Diffusion for Inverse Problems cites this paper.

Dual Ascent Diffusion for Inverse Problems Generative modeling of protein ensembles guided by crystallographic electron densities

Reference 26

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Observation bc76ca27-b095-4ded-a9eb-9a2a033866c0 · inbound

Adaptive Multimodal Protein Plug-and-Play with Diffusion-Based Priors cites this paper.

Adaptive Multimodal Protein Plug-and-Play with Diffusion-Based Priors Generative modeling of protein ensembles guided by crystallographic electron densities

Reference 15

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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