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Paper Citation Record · LEDGER

Formal Verification of Unknown Dynamical Systems via Gaussian Process Regression

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2201.00655.

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

pith.paper-citation-record.v1
2201.00655 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 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:08:32.963014Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T11:36:02.247636Z

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 68cd1d37-8737-46d8-a838-d899989a0582 · inbound

Temporal Logic Control for Nonlinear Stochastic Systems Under Unknown Disturbances cites this paper.

Temporal Logic Control for Nonlinear Stochastic Systems Under Unknown Disturbances Formal Verification of Unknown Dynamical Systems via Gaussian Process Regression

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-11T15:08:32.963014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:08:32.963014Z digest=sha256:b9c565737bca43a8f08fe77ea12aeab245e12bd16dc8eaaea123488b07614f8e

Observation 61707753-8909-48de-9ab2-cadbd513c762 · inbound

On the Optimality of Uncertain MDP Abstractions cites this paper.

On the Optimality of Uncertain MDP Abstractions Formal Verification of Unknown Dynamical Systems via Gaussian Process Regression

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:36:02.255743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-10T13:48:05.851529Z digest=sha256:7c1e9a7713bf60df0b4b5d2eb176583e19a333e3f6bff50d1a484d867c7f6c2a