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Paper Citation Record · LEDGER

Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2107.08024.

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

pith.paper-citation-record.v1
2107.08024 v1

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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:27:51.474379Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T22:12:51.762605Z

Reference resolution

0 of 0 outbound references displayed

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

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 83d960ab-4e86-4638-be2c-034d06a10727 · inbound

Meta-learning Structure-Preserving Dynamics cites this paper.

Meta-learning Structure-Preserving Dynamics Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-18T22:12:51.765767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-18T22:12:25.360812Z digest=sha256:fc0cd2ab646829726f744c2594221eeedff917edd939cf2685df688f53cfe78a

Observation 4f6cf274-50c3-4fbf-8202-9258cef671e0 · inbound

Energy-Structured Latent World Models with Neural Time Fields for Physically Constistent Open-World Motion Planning cites this paper.

Energy-Structured Latent World Models with Neural Time Fields for Physically Constistent Open-World Motion Planning Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-15T14:27:51.474379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T14:27:51.474379Z digest=sha256:fc083ed0abbeb0a853e3b3d5c3568e76f887a04dba66ae9eff47d9d4ad0460be