Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A machine learning framework for data driven acceleration of computations of differential equations
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1807.09519.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-26T12:44:01.793834Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
19
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 2e40b654-de0b-45af-8eef-6c74a3189e86 · inbound
Gaussian process surrogate with physical law-corrected prior for multi-coupled PDEs defined on irregular geometry cites this paper.
Gaussian process surrogate with physical law-corrected prior for multi-coupled PDEs defined on irregular geometry A machine learning framework for data driven acceleration of computations of differential equations
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T20:31:50.621696Z
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.
Observation 4b75305a-0382-48be-b5e5-619942efe9d8 · inbound
Accelerating Simulation and Optimisation of Cyclic Adsorption Processes with Differentiable Programming cites this paper.
Accelerating Simulation and Optimisation of Cyclic Adsorption Processes with Differentiable Programming A machine learning framework for data driven acceleration of computations of differential equations
Reference 26
- Resolution
- verified exact
- local_arxiv, observed 2026-06-26T12:49:29.018667Z
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.