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Paper Citation Record · LEDGER

Sobolev Training for Physics Informed Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2101.08932.

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

pith.paper-citation-record.v1
2101.08932 v2

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

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:06:58.774491Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T17:06:58.949868Z

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 886b3239-91a3-45c3-9063-805ef423e4ca · inbound

Neural Shortest Path for Surface Reconstruction from Point Clouds cites this paper.

Neural Shortest Path for Surface Reconstruction from Point Clouds Sobolev Training for Physics Informed Neural Networks

Reference 50

Resolution
metadata mismatch
local_arxiv, observed 2026-08-08T17:06:58.953440Z

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=2026-08-08T17:06:58.774491Z digest=sha256:c653da424c9bce027845fe487a8b975c235d1c8f8ae8aa23fa7d0ff039a4aa85

Observation 6931992d-bcfb-4ab2-adbc-45a421ceca26 · inbound

Introduction to optimization methods for training SciML models cites this paper.

Introduction to optimization methods for training SciML models Sobolev Training for Physics Informed Neural Networks

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-03T10:27:48.487293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:27:48.487293Z digest=sha256:e1f19b0bf417a949446ce31e04d1ef58e3dfe30106c7c0d61e4a570a4f065090