Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A data-driven Koopman model predictive control framework for nonlinear flows
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1804.05291.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T15:00:09.982826Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-14T05:28:30.504757Z
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 9fece94a-2e58-43cd-ab5b-e339c593844c · inbound
Koopman Representations of Dynamic Systems with Control cites this paper.
Koopman Representations of Dynamic Systems with Control A data-driven Koopman model predictive control framework for nonlinear flows
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T15:00:09.982826Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 06e5b2b4-74aa-42e5-9c67-0e6d490e64b5 · inbound
A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings cites this paper.
A Koopman-based framework for forecasting the spatiotemporal evolution of chaotic dynamics with nonlinearities modeled as exogenous forcings A data-driven Koopman model predictive control framework for nonlinear flows
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T10:07:34.598352Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a0984e01-96b9-44c0-9c65-4e7c25438440 · inbound
Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition cites this paper.
Learning Koopman Eigenfunctions and Invariant Subspaces from Data: Symmetric Subspace Decomposition A data-driven Koopman model predictive control framework for nonlinear flows
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-08-14T05:28:30.622161Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.