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Paper Citation Record · LEDGER

Convergence of Implicit Gradient Descent for Training Two-Layer Physics-Informed Neural Networks

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2407.02827.

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

pith.paper-citation-record.v1
2407.02827 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:34:57.482807Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T16:44:53.907740Z

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 17392fd5-aae9-4dca-9f1f-f9ea501e75c2 · inbound

Non-Asymptotic Analysis of Projected Gradient Descent for Physics-Informed Neural Networks cites this paper.

Non-Asymptotic Analysis of Projected Gradient Descent for Physics-Informed Neural Networks Convergence of Implicit Gradient Descent for Training Two-Layer Physics-Informed Neural Networks

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-15T22:34:57.482807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:34:57.482807Z digest=sha256:a4e3d7a47da41fc2a0e836057727efd9d5b294a6f1cfa85a64382c4eba290101

Observation f0d25daf-e95e-412e-b0f3-90f4a79faf62 · inbound

Convergence of Stochastic Gradient Methods for Wide Two-Layer Physics-Informed Neural Networks for the Poisson Equation cites this paper.

Convergence of Stochastic Gradient Methods for Wide Two-Layer Physics-Informed Neural Networks for the Poisson Equation Convergence of Implicit Gradient Descent for Training Two-Layer Physics-Informed Neural Networks

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-08-15T16:44:53.915304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T16:44:53.861579Z digest=sha256:097463df2f78b2e3973e444af3700b9ebce6186ba06e308b5b6aed194ea02e03

Observation dad978a1-3591-4973-ad17-d781bfefec44 · inbound

The Differential Neural Tangent Kernel and Its Positivity cites this paper.

The Differential Neural Tangent Kernel and Its Positivity Convergence of Implicit Gradient Descent for Training Two-Layer Physics-Informed Neural Networks

Reference 47

Resolution
unresolved
no resolver link, observed 2026-07-14T13:34:45.196896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T13:34:45.196896Z digest=sha256:f4d0ece2f2abff3ce0e4b4f70d0ef38d4c0daef9c90ca291a4c28b5585e88bc1