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Paper Citation Record · LEDGER

Tackling the Curse of Dimensionality with Physics-Informed Neural Networks

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2307.12306.

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

pith.paper-citation-record.v1
2307.12306 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:24:51.199320Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T00:56:24.238950Z

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 bd37cd8a-cff5-4a0e-9694-41ccb6aca829 · inbound

Adaptive Neural Network Subspace Method for Solving Partial Differential Equations with High Accuracy cites this paper.

Adaptive Neural Network Subspace Method for Solving Partial Differential Equations with High Accuracy Tackling the Curse of Dimensionality with Physics-Informed Neural Networks

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-11T23:24:51.199320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T23:24:51.199320Z digest=sha256:f36ec6b29bcae2122635971a5820908c667906814d2a106aaead3db218b40ca1

Observation 6d29e834-95da-4d8e-a6b0-6b90b5e5cd56 · inbound

Physics-Informed Residuals for Adaptive Mesh Refinement in Finite-Difference PDE Solvers cites this paper.

Physics-Informed Residuals for Adaptive Mesh Refinement in Finite-Difference PDE Solvers Tackling the Curse of Dimensionality with Physics-Informed Neural Networks

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-02T00:56:24.240846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T13:14:45.284507Z digest=sha256:6025636f7c96dd14f828cec55dbb27fd418975e43f7ad419211f48925dfa6047