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Paper Citation Record · LEDGER

Achieving High Accuracy with PINNs via Energy Natural Gradients

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2302.13163.

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

pith.paper-citation-record.v1
2302.13163 v2

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 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T12:43:35.864880Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e9705032-6e0b-4396-8b59-8ac801dfbfd8 · inbound

A physics-informed neural network approach to the point defect model for electrochemical oxide film growth cites this paper.

A physics-informed neural network approach to the point defect model for electrochemical oxide film growth Achieving High Accuracy with PINNs via Energy Natural Gradients

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-04T12:43:35.864880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T12:43:35.864880Z digest=sha256:2d3c357df91c491d75ee90aa878ae5fcc13cecec245c904a6234d66f375ba298

Observation bc83d8c3-0bf6-4073-9d29-efb71ab8fafb · inbound

Natural gradient descent with momentum cites this paper.

Natural gradient descent with momentum Achieving High Accuracy with PINNs via Energy Natural Gradients

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:15:10.006489Z

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.

source=pdf_text observed=2026-05-10T11:10:11.995285Z digest=sha256:7e10c8914cce8149a046dc50f0e7989048ed83f1500fdb3a0ac37a27721ab65e

Observation a8ba6cb4-fdd1-46d4-ae47-b5cebc70c221 · inbound

Exact Boundary Enforcement Along Implicit Geometries for Physics-Informed, Deep Learning Problems in Continuum Mechanics cites this paper.

Exact Boundary Enforcement Along Implicit Geometries for Physics-Informed, Deep Learning Problems in Continuum Mechanics Achieving High Accuracy with PINNs via Energy Natural Gradients

Reference 46

Resolution
malformed identifier
arxiv_id, observed 2026-06-29T14:13:29.972326Z

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.

source=pdf_text observed=2026-06-29T14:11:56.439388Z digest=sha256:5333e4fa9f6147a724ee43d1830a7958deee5969ec5825a89c21408088860a58