Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Variance representations and convergence rates for data-driven approximations of Koopman operators
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2402.02494.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:25:45.886114Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-28T23:22:47.032180Z
Reference resolution
0 of 0 outbound references displayed
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- malformed identifier0
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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 b5783bbb-1b32-4db1-ac19-2b94c08070fd · inbound
Two-component controller design to safeguard data-driven predictive control cites this paper.
Two-component controller design to safeguard data-driven predictive control Variance representations and convergence rates for data-driven approximations of Koopman operators
Reference 61
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:25:45.886114Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a9d4ef65-5aed-4eaf-a5bb-3c13ba5f6860 · inbound
Sample-Efficient Online Control Policy Learning with Real-Time Recursive Model Updates cites this paper.
Sample-Efficient Online Control Policy Learning with Real-Time Recursive Model Updates Variance representations and convergence rates for data-driven approximations of Koopman operators
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T21:05:05.127093Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation daa201df-c665-4daf-aff1-b3f052366d90 · inbound
Residual SCI Upper Bounds And Lower Witnesses For Koopman Approximate Point Spectra In $L^p$ For $1<p<\infty$: Extended Version cites this paper.
Residual SCI Upper Bounds And Lower Witnesses For Koopman Approximate Point Spectra In $L^p$ For $1<p<\infty$: Extended Version Variance representations and convergence rates for data-driven approximations of Koopman operators
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T15:56:34.609743Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 4aa110d5-e7dd-4eda-aeba-fbf2ee265773 · inbound
Koopman for stochastic dynamics: error bounds for kernel extended dynamic mode decomposition cites this paper.
Koopman for stochastic dynamics: error bounds for kernel extended dynamic mode decomposition Variance representations and convergence rates for data-driven approximations of Koopman operators
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T20:28:23.851073Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation ec27d175-383a-4f53-9423-ff7b0d1641c1 · inbound
Flow map learning in nonlinear vector autoregressive models: influence of the feature-library structure on the training error cites this paper.
Flow map learning in nonlinear vector autoregressive models: influence of the feature-library structure on the training error Variance representations and convergence rates for data-driven approximations of Koopman operators
Reference 100
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:22:47.033723Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.