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Paper Citation Record · LEDGER

Modeling Unknown Stochastic Dynamical System Subject to External Excitation

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.15747.

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

pith.paper-citation-record.v1
2406.15747 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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:36:08.469492Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T16:10:29.840705Z

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 fa9e7cdb-9569-45e1-977c-7c2ab68f1902 · inbound

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network cites this paper.

Learning Stochastic Hamiltonian Systems via Stochastic Generating Function Neural Network Modeling Unknown Stochastic Dynamical System Subject to External Excitation

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-08-06T16:10:29.970807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T16:10:28.719779Z digest=sha256:1e0c4e59584411035cf19371841cf7472db97440633eab2fd30d341555810175

Observation 3c368879-8fc1-45bd-9986-d2aa214b39db · inbound

Generative AI Models for Learning Flow Maps of Stochastic Dynamical Systems in Bounded Domains cites this paper.

Generative AI Models for Learning Flow Maps of Stochastic Dynamical Systems in Bounded Domains Modeling Unknown Stochastic Dynamical System Subject to External Excitation

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T16:36:08.469492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:36:08.469492Z digest=sha256:f17a7704406681ca2cba9f83a5c2cdcd963c87a596be594c78a986ad9c2599e5