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Paper Citation Record · LEDGER

Robust Regression with Highly Corrupted Data via Physics Informed Neural Networks

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2210.10646.

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

pith.paper-citation-record.v1
2210.10646 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T21:21:40.972142Z

measured 1 of 1 external citation measurements

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

Source: pith, 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

1
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 4199d28f-1205-4373-bc83-117b05661433 · inbound

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion cites this paper.

Physics-Informed Neural Networks in Clean Combustion: A Pathway to Sustainable Aerospace Propulsion Robust Regression with Highly Corrupted Data via Physics Informed Neural Networks

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-04T21:21:40.972142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:21:40.972142Z digest=sha256:6826eba8819df33e28210ff2fc5c5f9b1276a34e429fe8b08d2c89b6e9b9a8e3

Observation 5cbec82f-df2c-4dd5-87aa-819ece49c7eb · inbound

naPINN: Noise-Adaptive Physics-Informed Neural Networks for Recovering Physics from Corrupted Measurement cites this paper.

naPINN: Noise-Adaptive Physics-Informed Neural Networks for Recovering Physics from Corrupted Measurement Robust Regression with Highly Corrupted Data via Physics Informed Neural Networks

Reference 2022

Resolution
metadata mismatch
local_arxiv, observed 2026-08-03T06:38:31.135494Z

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=2026-08-03T06:36:14.821776Z digest=sha256:02b0003ac0f2536d909a8aeb1abb19fa19d1cd27e8930c0301063004d504eeed