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Paper Citation Record · LEDGER

Solving Inverse Problems in Steady-State Navier-Stokes Equations using Deep Neural Networks

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2008.13074.

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

pith.paper-citation-record.v1
2008.13074 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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:13:21.305754Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T07:32:42.788582Z

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 a3fc4a9c-afdd-4620-b75f-6f1f867172ac · inbound

TAEN: A Model-Constrained Tikhonov Autoencoder Network for Forward and Inverse Problems cites this paper.

TAEN: A Model-Constrained Tikhonov Autoencoder Network for Forward and Inverse Problems Solving Inverse Problems in Steady-State Navier-Stokes Equations using Deep Neural Networks

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-23T07:32:42.791673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-23T07:31:22.510665Z digest=sha256:20882a3100996eb53e64971ab217367d34c85d1e1b956f81be3d9bcde597d0bc

Observation 6d460cc5-00ee-4372-b104-a4bfa80634e1 · inbound

Inferring viscoplastic models from velocity fields: a physics-informed neural network approach cites this paper.

Inferring viscoplastic models from velocity fields: a physics-informed neural network approach Solving Inverse Problems in Steady-State Navier-Stokes Equations using Deep Neural Networks

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-15T19:13:21.305754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:13:21.305754Z digest=sha256:d901ead3cafdd9b586d818f1226d2ae6cb9951b02abea524bd4d4c36b6edb00e