Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A local squared Wasserstein-2 method for efficient reconstruction of models with uncertainty
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2406.06825.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T23:04:41.494127Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T01:12:20.522441Z
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 03d8781d-f4b6-41fb-a89e-2ced639b5a52 · inbound
Error estimation for quasi-Monte Carlo cites this paper.
Error estimation for quasi-Monte Carlo A local squared Wasserstein-2 method for efficient reconstruction of models with uncertainty
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T23:04:41.494127Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ba95a7e5-99d6-462c-9919-c4fcb365c560 · inbound
Reconstructing Noisy Gene Regulation Dynamics Using Extrinsic-Noise-Driven Neural Stochastic Differential Equations cites this paper.
Reconstructing Noisy Gene Regulation Dynamics Using Extrinsic-Noise-Driven Neural Stochastic Differential Equations A local squared Wasserstein-2 method for efficient reconstruction of models with uncertainty
Reference 45
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T01:12:20.524386Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation a82685c7-98b5-4785-94f7-f706b9594693 · inbound
A generalized Wasserstein-2 distance approach for efficient reconstruction of random field models using stochastic neural networks cites this paper.
A generalized Wasserstein-2 distance approach for efficient reconstruction of random field models using stochastic neural networks A local squared Wasserstein-2 method for efficient reconstruction of models with uncertainty
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:42:58.000247Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.