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Paper Citation Record · LEDGER

Kernel Sum of Squares for Data Adapted Kernel Learning of Dynamical Systems from Data: A global optimization approach

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2408.06465.

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

pith.paper-citation-record.v1
2408.06465 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 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:32:12.910761Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T12:14:11.766105Z

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 9e89d5ab-4b55-40ad-8d4d-5fbc5b01457b · inbound

Kernel Methods for the Approximation of the Eigenfunctions of the Koopman Operator cites this paper.

Kernel Methods for the Approximation of the Eigenfunctions of the Koopman Operator Kernel Sum of Squares for Data Adapted Kernel Learning of Dynamical Systems from Data: A global optimization approach

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-11T10:32:12.910761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:32:12.910761Z digest=sha256:a3d4f8fa1f61571f1ea61eda7c9293f20da3a6e05dac9e320f56df6a71639424

Observation a6cf10b9-375f-48b6-a18f-1706609986ba · inbound

Kernel-Based LMI Approaches to Solving the Hamilton-Jacobi-Bellman Equation and Nonlinear Optimal Control cites this paper.

Kernel-Based LMI Approaches to Solving the Hamilton-Jacobi-Bellman Equation and Nonlinear Optimal Control Kernel Sum of Squares for Data Adapted Kernel Learning of Dynamical Systems from Data: A global optimization approach

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-21T12:14:11.768353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-21T12:11:34.123475Z digest=sha256:7106588b8292c10d502e15bb2c0e09ac771506a18207863349e5bd174049f434