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Paper Citation Record · LEDGER

A deep learning energy method for hyperelasticity and viscoelasticity

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2201.08690.

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

pith.paper-citation-record.v1
2201.08690 v1

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 2026-08-07T10:48:10.354962Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T22:40:13.452581Z

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 8ce2eb44-95b7-4b3d-bdcc-b917f09d8d8e · inbound

Solving engineering eigenvalue problems with neural networks using the Rayleigh quotient cites this paper.

Solving engineering eigenvalue problems with neural networks using the Rayleigh quotient A deep learning energy method for hyperelasticity and viscoelasticity

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T10:48:10.354962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:48:10.354962Z digest=sha256:0d0df85e2f4d77fac8b39680acaf5b98600562adb8d527df3967d9779983d192

Observation f85a2de9-37ff-4cfa-bd55-3ac407a33d2c · inbound

Variational volume reconstruction with the Deep Ritz Method cites this paper.

Variational volume reconstruction with the Deep Ritz Method A deep learning energy method for hyperelasticity and viscoelasticity

Reference 1

Resolution
metadata mismatch
local_arxiv, observed 2026-08-05T22:40:13.457129Z

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=arxiv_source observed=2026-08-05T22:40:09.097985Z digest=sha256:27d97e3ff7d83a4f44866418ddc140c4f791cc6627c5702e2a30a46ff27d2cc6