Paper Citation Record · LEDGER

Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.06308.

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

pith.paper-citation-record.v1
2410.06308 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 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:57:13.457775Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T20:52:38.096032Z

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 6727ef35-05fd-49ce-8220-d500938e6fb1 · inbound

Learn Singularly Perturbed Solutions via Homotopy Dynamics cites this paper.

Learn Singularly Perturbed Solutions via Homotopy Dynamics Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T18:57:13.457775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01525e0e-14c6-46f9-ae30-78cca8a480d3 · inbound

Complex Physics-Informed Neural Network cites this paper.

Complex Physics-Informed Neural Network Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-08T21:06:33.447415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea313a96-e5d7-4241-baa1-3aa92462eac6 · inbound

Spectral connvergece of random feature method in one dimension cites this paper.

Spectral connvergece of random feature method in one dimension Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T18:50:10.900263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04cc1c4d-b456-445a-a3d5-1227484d32f9 · inbound

Taming the Loss Landscape of PINNs with Noisy Feynman-Kac Supervision: Operator Preconditioning and Non-Asymptotic Error Bounds cites this paper.

Taming the Loss Landscape of PINNs with Noisy Feynman-Kac Supervision: Operator Preconditioning and Non-Asymptotic Error Bounds Quantifying Training Difficulty and Accelerating Convergence in Neural Network-Based PDE Solvers

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-06-28T20:52:38.098168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.