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Paper Citation Record · LEDGER

Improved deep learning of chaotic dynamical systems with multistep penalty losses

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.05572.

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

pith.paper-citation-record.v1
2410.05572 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 2026-08-06T06:34:29.942622+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T23:18:20.863855Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T00:05:31.339149Z

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 7b45d7d3-4799-4324-a98c-178e3a69b338 · inbound

A Weak Penalty Neural ODE for Learning Chaotic Dynamics from Noisy Time Series cites this paper.

A Weak Penalty Neural ODE for Learning Chaotic Dynamics from Noisy Time Series Improved deep learning of chaotic dynamical systems with multistep penalty losses

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-18T00:05:31.341905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-18T00:05:02.934722Z digest=sha256:dbc19d34a63a65695b21521d8121e02d3665bf8fdd0014a0966dd69fa0eaf2f0

Observation a977aa48-a051-40a1-828a-7d4d777be286 · inbound

A Weak Penalty Neural ODE for Learning Chaotic Dynamics from Noisy Time Series cites this paper.

A Weak Penalty Neural ODE for Learning Chaotic Dynamics from Noisy Time Series Improved deep learning of chaotic dynamical systems with multistep penalty losses

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-03T23:18:20.863855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T23:18:20.863855Z digest=sha256:3ba6eba117c8eadbce7eaf5e09e8633c2cb9798faf4d5039361a51cb2168f2e9