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Paper Citation Record · LEDGER

A Structure-Preserving Domain Decomposition Method for Data-Driven Modeling

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.05571.

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

pith.paper-citation-record.v1
2406.05571 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:33:51.155916Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T02:11:15.878364Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation ee88b84a-a7f4-4ea1-9217-591dc5e2a9b2 · inbound

Structure-Preserving Digital Twins via Conditional Neural Whitney Forms cites this paper.

Structure-Preserving Digital Twins via Conditional Neural Whitney Forms A Structure-Preserving Domain Decomposition Method for Data-Driven Modeling

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-05T22:33:51.155916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9132b2b7-9416-4b58-93bc-aff69bf5f78c · inbound

Physics-informed sensor coverage through structure preserving machine learning cites this paper.

Physics-informed sensor coverage through structure preserving machine learning A Structure-Preserving Domain Decomposition Method for Data-Driven Modeling

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-04T17:58:16.284845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:58:16.284845Z digest=sha256:d495eaf457038de06284dcbfc8f8d4fb86c24bcca8ddd6c775d2f634e461e58d

Observation e57ab901-8907-44ff-8be5-b99e5391f386 · inbound

Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs cites this paper.

Structure-Preserving Learning Improves Geometry Generalization in Neural PDEs A Structure-Preserving Domain Decomposition Method for Data-Driven Modeling

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-03T05:22:11.747812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:22:11.747812Z digest=sha256:a764bd9c79264dd0f89d773d7a28009f69d56e02a1fe3a4d01d76f9418a1668a

Observation a389fb47-cebe-4412-a765-8a02516bfbce · inbound

A Hybridizable Neural Time Integrator for Stable Autoregressive Forecasting cites this paper.

A Hybridizable Neural Time Integrator for Stable Autoregressive Forecasting A Structure-Preserving Domain Decomposition Method for Data-Driven Modeling

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:14:46.543467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T00:12:58.131638Z digest=sha256:8762a7484a0fd31c565fe7efe66c3bd143fa6bba0e6324207e77069fa0d372a7

Observation c7d7b00c-7d86-4b2e-90fe-6f6adeb33e22 · inbound

A meshfree exterior calculus for generalizable and data-efficient learning of physics from point clouds cites this paper.

A meshfree exterior calculus for generalizable and data-efficient learning of physics from point clouds A Structure-Preserving Domain Decomposition Method for Data-Driven Modeling

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-05-12T02:11:15.880524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-12T02:09:01.875110Z digest=sha256:dc0fc7bafdb18acbb7deb96c5696f25a02c763d8e08b9bbf958f7eec14c2ff4b