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Paper Citation Record · LEDGER

Physics-Informed Neural Nets for Control of Dynamical Systems

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2104.02556.

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

pith.paper-citation-record.v1
2104.02556 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:42:34.198513Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T00:16:15.729268Z

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 1fb4645d-5b0b-48e4-a543-199ff2aa4dc0 · inbound

Deep Operator Networks for Bayesian Parameter Estimation in PDEs cites this paper.

Deep Operator Networks for Bayesian Parameter Estimation in PDEs Physics-Informed Neural Nets for Control of Dynamical Systems

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-10T19:06:10.561620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-10T19:06:10.149628Z digest=sha256:d562299f7e58f65170ea279180e383a45c3ac34b3c7dd7666448c0f723ed31d3

Observation 891e46b1-ab26-4f99-aca1-55647ae08dcf · inbound

Modelling of Underwater Vehicles using Physics-Informed Neural Networks with Control cites this paper.

Modelling of Underwater Vehicles using Physics-Informed Neural Networks with Control Physics-Informed Neural Nets for Control of Dynamical Systems

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-16T05:42:34.198513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:42:34.198513Z digest=sha256:1b65766d0f315145a557f47087d2c3bf0f5f8e327e99d442e3b59eba8552b757

Observation 801b1d5b-74d8-47c8-8c7a-cff8bb39787a · inbound

Controlling synchronization dynamics via physics-informed neural networks cites this paper.

Controlling synchronization dynamics via physics-informed neural networks Physics-Informed Neural Nets for Control of Dynamical Systems

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-03T13:12:21.562644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:12:21.562644Z digest=sha256:c55290950a62d01f0cf4b6e227efd8063d086eeb24998fe7b412f83b9fa2062f