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Paper Citation Record · LEDGER

Symplectic Neural Networks Based on Dynamical Systems

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2408.09821.

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

pith.paper-citation-record.v1
2408.09821 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:11:45.316551Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T20:37:34.150491Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
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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 e31c27d6-91d5-458a-9c43-4c1f976238a5 · inbound

Learning mechanical systems from real-world data using discrete forced Lagrangian dynamics cites this paper.

Learning mechanical systems from real-world data using discrete forced Lagrangian dynamics Symplectic Neural Networks Based on Dynamical Systems

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T14:11:45.316551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:11:45.316551Z digest=sha256:2ad015c744511a1ad80df91e9c7fcab77b5b4563bc3908fd02788b7a920643a5

Observation 8d92fe82-15e6-40ce-9d36-e973a32f2eb2 · inbound

Chaoticus: a parallel approach to the computation of chaos indicators cites this paper.

Chaoticus: a parallel approach to the computation of chaos indicators Symplectic Neural Networks Based on Dynamical Systems

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:09.345596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:15:09.345596Z digest=sha256:98d50774999bb18c6a2e80adeb42da32b5e9599bd81aba971264e2e1a8ba1b00

Observation fa5616d3-f5c0-467a-aed5-443851269b66 · inbound

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts cites this paper.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Symplectic Neural Networks Based on Dynamical Systems

Reference 64

Resolution
verified exact
local_arxiv, observed 2026-07-10T20:37:34.152085Z

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=2026-07-10T20:34:14.693049Z digest=sha256:65f51ef94ea41856b40c4670ac38f17fbe20154fe0f80257255f3183496b371f

Observation 349864a7-0652-46fa-9cdf-5029b2f35139 · inbound

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts cites this paper.

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts Symplectic Neural Networks Based on Dynamical Systems

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-02T08:18:18.194069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T08:18:18.194069Z digest=sha256:e591db51743e088de93178bf31ee2e2af222476655ea64e780307cff3205b37f