Paper Citation Record · LEDGER

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

As of 17 August 2026, this Paper Citation Record lists 4 of 4 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 4 of 4 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:26:07.843127Z

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

4 of 4 outbound references displayed

verified exact0
verified fuzzy3
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

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

Outbound references

Observation 95504072-8d30-4645-9255-5d7364a97ff0 · outbound

This paper cites Physics-informed neural networks.

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

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:26:07.934983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9d53231d-dfd8-40a9-83a4-73d49be574f6 · outbound

This paper cites an unresolved cited work.

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

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-12T11:26:07.916336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 14922860-956d-4354-804b-455aba1a0802 · outbound

This paper cites Compatibility conditions for time-dependent partial differential equations and the rate of convergence of chebyshev and fourier spectral methods.

Physics Informed Neural Networks (PINNs) as intelligent computing technique for solving partial differential equations: Limitation and Future prospects Compatibility conditions for time-dependent partial differential equations and the rate of convergence of chebyshev and fourier spectral methods

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:26:07.882967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e28e9fc4-912c-4708-9fc8-4ef7a8ef8b46 · outbound

This paper cites For instance, in high Reynolds number wall-bounded turbulence with multiscale phenomenon, anisotropic grids within the boundary layer are often indispensable.

Physics Informed Neural Networks (PINNs) as intelligent computing technique for solving partial differential equations: Limitation and Future prospects For instance, in high Reynolds number wall-bounded turbulence with multiscale phenomenon, anisotropic grids within the boundary layer are often indispensable

Reference 5000

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:26:07.899750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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.

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.

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 2026-08-17T06:30:58.91139+00:00.

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 2026-08-17T06:30:58.91139+00:00.

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 2026-08-17T06:30:58.91139+00:00.

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 2026-08-17T06:30:58.91139+00:00.