Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Artificial Neural Networks for Solving Ordinary and Partial Differential Equations
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:physics/9705023.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T07:32:30.486756Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-03T13:38:19.058791Z
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 0968042d-e724-4cc0-ae8f-9fdb929b64db · inbound
LieSolver: PDE-Constrained Learning for IBVPs via Lie Symmetries cites this paper.
LieSolver: PDE-Constrained Learning for IBVPs via Lie Symmetries Artificial Neural Networks for Solving Ordinary and Partial Differential Equations
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T07:32:30.486756Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4f7ffd51-6675-48b5-95c3-89bd12f2d3dd · inbound
Physics-Informed Neural Networks for Solving Two-Flavor Neutrino Oscillations in Vacuum and Matter Environments for Atmospheric and Reactor Neutrinos cites this paper.
Physics-Informed Neural Networks for Solving Two-Flavor Neutrino Oscillations in Vacuum and Matter Environments for Atmospheric and Reactor Neutrinos Artificial Neural Networks for Solving Ordinary and Partial Differential Equations
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T14:16:21.646024Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f6dcf5c9-651b-404a-ac6c-97600c6103fa · inbound
Physics-Informed Neural Networks for Solving Two-Flavor Neutrino Oscillations in Vacuum and Matter Environments for Atmospheric and Reactor Neutrinos cites this paper.
Physics-Informed Neural Networks for Solving Two-Flavor Neutrino Oscillations in Vacuum and Matter Environments for Atmospheric and Reactor Neutrinos Artificial Neural Networks for Solving Ordinary and Partial Differential Equations
Reference 34
- Resolution
- verified exact
- local_arxiv, observed 2026-05-14T22:18:04.114160Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 8aade0e8-82fb-405a-bb89-86689b30f14b · inbound
Neural-network solution of subtracted three-body Faddeev integral equations near the Efimov limit cites this paper.
Neural-network solution of subtracted three-body Faddeev integral equations near the Efimov limit Artificial Neural Networks for Solving Ordinary and Partial Differential Equations
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T07:47:45.111570Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 429c5f0a-b4e0-42f0-82d1-ec229952a3df · inbound
Hierarchical Framework of Runaway Electrons using Deep Learning cites this paper.
Hierarchical Framework of Runaway Electrons using Deep Learning Artificial Neural Networks for Solving Ordinary and Partial Differential Equations
Reference 30
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T13:38:19.060304Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.