Paper Citation Record · LEDGER

First Order System Least Squares Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2409.20264.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2409.20264 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T16:00:55.839526Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-23T02:02:23.089302Z

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 28f9adbf-d213-40a3-9901-c834bbebc8b3 · inbound

A posteriori certification of PDE approximations with particular application to neural networks cites this paper.

A posteriori certification of PDE approximations with particular application to neural networks First Order System Least Squares Neural Networks

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-23T02:02:23.091449Z

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 6458cc46-749f-4cb6-94dc-adb1de683124 · inbound

A deep first-order system least squares method for the obstacle problem cites this paper.

A deep first-order system least squares method for the obstacle problem First Order System Least Squares Neural Networks

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-05T16:00:55.839526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 515664e7-9637-433d-854e-254eb7a2e1ee · inbound

Neural Very Weak Formulations enabling Hardware-Oriented deep PDE solvers cites this paper.

Neural Very Weak Formulations enabling Hardware-Oriented deep PDE solvers First Order System Least Squares Neural Networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T02:03:20.464755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58cb26ba-286e-41be-bb78-468cac8ad695 · inbound

Non-Asymptotic Variational Learning for Monotone Nonlinear Multiscale Elliptic Equations: Scale-Robust Primal-Dual Bounds and Strong-Form Statistical Ill-Conditioning cites this paper.

Non-Asymptotic Variational Learning for Monotone Nonlinear Multiscale Elliptic Equations: Scale-Robust Primal-Dual Bounds and Strong-Form Statistical Ill-Conditioning First Order System Least Squares Neural Networks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T22:37:46.809625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.