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Paper Citation Record · LEDGER

Deep Neural Cellular Potts Models

As of 19 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 1 inbound Pith citation observation for arXiv:2502.02129.

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

pith.paper-citation-record.v1
2502.02129 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T13:18:51.007404Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T21:34:53.898736Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

17 of 17 outbound references displayed

  • verified exact0
  • verified fuzzy11
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fe79203d-b4c4-42a4-aba0-5863c265eea3 · outbound

This paper cites an unresolved cited work.

Deep Neural Cellular Potts Models Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-09T13:18:51.097872Z

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 f9c84433-fa81-4eec-8e13-34a99f77e4ef · outbound

This paper cites The sampler uses a proposal distribution where first, P lattice sites are independently and uniformly sampled from the boundary of cells.

Deep Neural Cellular Potts Models The sampler uses a proposal distribution where first, P lattice sites are independently and uniformly sampled from the boundary of cells

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:18:51.077868Z

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 642b5b79-ecde-4039-b9f0-81ae8acbbd41 · outbound

This paper cites and Glazier, J.

Deep Neural Cellular Potts Models and Glazier, J

Reference 3

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.

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Observation 3f0f2e0d-a040-4c3a-a46a-ba9cd1ae8174 · outbound

This paper cites Deep residual learning for image recognition.

Deep Neural Cellular Potts Models Deep residual learning for image recognition

Reference 4

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.

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Observation 03263266-4d1f-4d42-a067-5f66c88e969c · outbound

This paper cites (2018) consist of 200 to 240 cells in 3D which amounts to about 8 cells along a diameter and about 40 cells in the cross-section.

Deep Neural Cellular Potts Models (2018) consist of 200 to 240 cells in 3D which amounts to about 8 cells along a diameter and about 40 cells in the cross-section

Reference 5

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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.

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Observation d2d99f19-e222-4853-8c44-155cb081b1a3 · outbound

This paper cites an unresolved cited work.

Deep Neural Cellular Potts Models Unresolved cited work

Reference 7

Resolution
unresolved
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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 23f58689-7297-41cc-bbfe-acbe929c71d6 · outbound

This paper cites an unresolved cited work.

Deep Neural Cellular Potts Models Unresolved cited work

Reference 8

Resolution
unresolved
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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 120d7e0d-0840-4116-b66c-3ef02f06b5d5 · outbound

This paper cites We distinguish the two scenarios a and b from Edelstein-Keshet & Xiao (2023), characterized by different contact energies between cells, which are laid out in tables 3 and.

Deep Neural Cellular Potts Models We distinguish the two scenarios a and b from Edelstein-Keshet & Xiao (2023), characterized by different contact energies between cells, which are laid out in tables 3 and

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:18:51.142412Z

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 cd8aab01-f424-4374-b328-574f9c2026a1 · outbound

This paper cites Notably, Hcase-specific(x) now took the form of an external potential Hcase-specific(x) = X i∈L µ(xi)ϕi (8) where µ(xi) can be considered the coupling strength to the potential ϕi.

Deep Neural Cellular Potts Models Notably, Hcase-specific(x) now took the form of an external potential Hcase-specific(x) = X i∈L µ(xi)ϕi (8) where µ(xi) can be considered the coupling strength to the potential ϕi

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:18:51.131582Z

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 f905d5f3-d757-4061-a546-c64a0e390f6b · outbound

This paper cites 12 Deep Neural Cellular Potts Models Table.

Deep Neural Cellular Potts Models 12 Deep Neural Cellular Potts Models Table

Reference 12

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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 561b6391-920c-402c-91dc-7359ac5533d9 · outbound

This paper cites How to Train Your Energy-Based Models.

Deep Neural Cellular Potts Models How to Train Your Energy-Based Models

Reference 1997

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unresolved
no resolver link, observed 2026-08-09T13:18:50.976768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 31753e28-13e6-4b31-ace2-473582da9132 · outbound

This paper cites Towards learned simulators for cell migration.

Deep Neural Cellular Potts Models Towards learned simulators for cell migration

Reference 2001

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:18:51.162728Z

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 3d55f34c-ae54-4353-b669-fa574ed3b215 · outbound

This paper cites and Garcia, C.

Deep Neural Cellular Potts Models and Garcia, C

Reference 2017

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:18:51.172507Z

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 c46bf811-f07d-4eda-9720-4e6c9598db5d · outbound

This paper cites Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.

Deep Neural Cellular Potts Models Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-09T13:18:50.949268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:18:50.949268Z digest=sha256:261454bbbc9c957b53bd102d3c246f96ef39721246866172f83b34bb6453a96f

Observation dc2081e2-05f2-4b28-b868-79ec2ff355f4 · outbound

This paper cites an unresolved cited work.

Deep Neural Cellular Potts Models Unresolved cited work

Reference 2020

Resolution
unresolved
raw_fallback, observed 2026-08-09T13:18:51.152515Z

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=pdf_text observed=2026-08-09T13:18:50.973053Z digest=sha256:b8e01faea23d5f4214761ddb79848165df78f5cd3b2fdbd3ce568a53222165d1

Observation 58032896-4964-4f08-8a2f-4a12578fa81e · outbound

This paper cites (Barbu & Zhu, 2020)).

Deep Neural Cellular Potts Models (Barbu & Zhu, 2020))

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:18:51.057299Z

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=pdf_text observed=2026-08-09T13:18:51.007404Z digest=sha256:9a1224d0abbdf82b749b2371d201c7e16565ce123dcf54a2f65932806951568e

Observation cd40fc2c-ba2c-4c40-8593-5228006e6b56 · outbound

This paper cites Elfwing, S., Uchibe, E., and Doya, K.

Deep Neural Cellular Potts Models Elfwing, S., Uchibe, E., and Doya, K

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T13:18:51.201621Z

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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Pith citing papers

Observation 34c66f54-efb5-430a-a9c0-e76655ed4f9e · inbound

Active Matter as a framework for living systems-inspired Robophysics cites this paper.

Active Matter as a framework for living systems-inspired Robophysics Deep Neural Cellular Potts Models

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-03T21:34:53.898736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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