Pith. sign in

Paper Citation Record · LEDGER

A neural network approach to learning solutions of a class of elliptic variational inequalities

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2411.18565.

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

pith.paper-citation-record.v1
2411.18565 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T12:12:35.100491Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T02:24:13.314455Z

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 3b0b0930-a2ce-4866-9594-a0c0d6739270 · inbound

A Single-Loop Bilevel Deep Learning Method for Optimal Control of Obstacle Problems cites this paper.

A Single-Loop Bilevel Deep Learning Method for Optimal Control of Obstacle Problems A neural network approach to learning solutions of a class of elliptic variational inequalities

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-03T12:12:35.100491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T12:12:35.100491Z digest=sha256:877b5e597ad905d5ff19c4b1d96af52f6be639f774de2b72ff0e50d3f3d43359

Observation 4a3697bb-b0fd-474c-9f8f-95a2846f0735 · inbound

Fourier Neural Operators with Least-Squares Readout Refit for Learning Random Obstacle-to-Solution Maps cites this paper.

Fourier Neural Operators with Least-Squares Readout Refit for Learning Random Obstacle-to-Solution Maps A neural network approach to learning solutions of a class of elliptic variational inequalities

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-08-04T01:51:30.002067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T02:19:37.613971Z digest=sha256:d7cd47a554af51ee6e1ad9cf6beb65b7eb5be8d2b013f1558fb0d22e57d1ac51