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Paper Citation Record · LEDGER

Model Reduction with Memory and the Machine Learning of Dynamical Systems

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1808.04258.

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

pith.paper-citation-record.v1
1808.04258 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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T12:18:49.576871Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T12:20:22.568609Z

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 6054ff1b-4cf6-450f-b549-14bcfc8f62e3 · inbound

Data-driven model reduction, Wiener projections, and the Koopman-Mori-Zwanzig formalism cites this paper.

Data-driven model reduction, Wiener projections, and the Koopman-Mori-Zwanzig formalism Model Reduction with Memory and the Machine Learning of Dynamical Systems

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-14T12:18:49.576871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:18:49.576871Z digest=sha256:e2273c646968f8719e004741a801078dd830beafd6400d5dae349c9b87279235

Observation 307e0d84-f5f1-476e-a701-1a033c886b81 · inbound

Stable Long-Horizon Neural ODE Reduced-Order Models via Learned Feedback for Biological Growth and Remodeling cites this paper.

Stable Long-Horizon Neural ODE Reduced-Order Models via Learned Feedback for Biological Growth and Remodeling Model Reduction with Memory and the Machine Learning of Dynamical Systems

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-07-04T22:58:41.970677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T12:18:04.301076Z digest=sha256:82e4d83ceacb04c64fd70a85487976b85958197ef877054bd9176b3d03f241d6