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Paper Citation Record · LEDGER

Physics Informed Neural Networks (PINNs) as intelligent computing technique for solving partial differential equations: Limitation and Future prospects

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2411.18240.

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

pith.paper-citation-record.v1
2411.18240 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:40:20.131830Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, 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

5
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 7dcf7f32-5ff4-4933-baf1-8e6227af0181 · inbound

Adaptive feature capture method for solving partial differential equations with near singular solutions cites this paper.

Adaptive feature capture method for solving partial differential equations with near singular solutions Physics Informed Neural Networks (PINNs) as intelligent computing technique for solving partial differential equations: Limitation and Future prospects

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T16:40:20.131830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:40:20.131830Z digest=sha256:a827f534d78aba8fec65896a261d74bf02219102866e7a0dc14da05f64844e1b

Observation 6811c49b-20d8-4846-98dc-dd1515517ea3 · inbound

Physics-informed Fourier Basis Neural Network for Fluid Mechanics cites this paper.

Physics-informed Fourier Basis Neural Network for Fluid Mechanics Physics Informed Neural Networks (PINNs) as intelligent computing technique for solving partial differential equations: Limitation and Future prospects

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T05:15:42.081951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:15:42.081951Z digest=sha256:da32ce94dd25eda926ade6d3f2387a5702bd8a77380228d1fbec09fb71842952

Observation f8e5a913-a718-4d66-8d02-a0099da47df4 · inbound

An adaptive wavelet-based PINN for problems with localized high-magnitude source cites this paper.

An adaptive wavelet-based PINN for problems with localized high-magnitude source Physics Informed Neural Networks (PINNs) as intelligent computing technique for solving partial differential equations: Limitation and Future prospects

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-09T04:50:11.691731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-07T07:14:05.096056Z digest=sha256:f33578f32c2a021c867d66e061698c5d1450ccc3ec65162799dc419ce61d64f9

Observation bcfe0714-f427-4926-b130-9a67e33b6805 · inbound

A numerical study into neural network surrogate model performance for uncertainty propagation cites this paper.

A numerical study into neural network surrogate model performance for uncertainty propagation Physics Informed Neural Networks (PINNs) as intelligent computing technique for solving partial differential equations: Limitation and Future prospects

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-19T19:02:43.611576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-19T18:57:56.373765Z digest=sha256:15af596139b99c62d4712ef81ad98a59736bb1654ddcff9a07eb4fa6ec8f2b41

Observation b32b4643-0d7b-4ee2-8f82-82ac1e8b9b1a · inbound

Bayesian Analysis Using a Constrained Mixture of Normal-Inverse-Gamma Models cites this paper.

Bayesian Analysis Using a Constrained Mixture of Normal-Inverse-Gamma Models Physics Informed Neural Networks (PINNs) as intelligent computing technique for solving partial differential equations: Limitation and Future prospects

Reference 172

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T11:49:50.830567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-26T07:35:00.683580Z digest=sha256:80b81e440dceb821194b8ffeaa41007cdc635189b47ae5c7927126bfe5b4b306

Observation 71a04c13-e20d-47db-afba-feb90da11e49 · inbound

A Physics-Informed Fourier-Wavelet Transformer for Multiscale Computational Fluid Dynamics Surrogate Modeling cites this paper.

A Physics-Informed Fourier-Wavelet Transformer for Multiscale Computational Fluid Dynamics Surrogate Modeling Physics Informed Neural Networks (PINNs) as intelligent computing technique for solving partial differential equations: Limitation and Future prospects

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-07-04T18:30:02.725426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-25T22:47:05.775339Z digest=sha256:8abb2241c01ce4bc52e020389a7aa380fd3eb29257a5bf17b1d47e84039e7e94