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Paper Citation Record · LEDGER

Learning Governing Equations of Unobserved States in Dynamical Systems

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.18572.

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

pith.paper-citation-record.v1
2404.18572 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T23:58:22.730638Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 490acbf8-4d65-4c2d-928b-dabec639b80b · inbound

Structural functional identifiability and model discovery in differential equation models cites this paper.

Structural functional identifiability and model discovery in differential equation models Learning Governing Equations of Unobserved States in Dynamical Systems

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-06-30T04:14:19.469684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-30T03:47:07.401052Z digest=sha256:5e6df33f3f46317593bc1b5d6602ea617279a5cc4f8f1b16bf416f9457d30901

Observation 17950dc5-dbda-4f7c-887b-58a74cb85da7 · inbound

RTS Smoother-Guided Learning of Physics-Based Neural Differential Models cites this paper.

RTS Smoother-Guided Learning of Physics-Based Neural Differential Models Learning Governing Equations of Unobserved States in Dynamical Systems

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-01T23:58:22.730638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T23:58:22.730638Z digest=sha256:c9a32e58ada56be009482a84688c6410e7a5f53bda16ca5d18dec0aa53ae3249