Paper Citation Record · LEDGER

Physics-informed KAN PointNet: Deep learning for simultaneous solutions to inverse problems in incompressible flow on numerous irregular geometries

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2504.06327.

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

pith.paper-citation-record.v1
2504.06327 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T20:59:04.410769Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T23:36:54.609582Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 61c36bb1-b5c3-4353-be38-e5a18f71587f · inbound

LNN-PINN: A Unified Physics-Only Training Framework with Liquid Residual Blocks cites this paper.

LNN-PINN: A Unified Physics-Only Training Framework with Liquid Residual Blocks Physics-informed KAN PointNet: Deep learning for simultaneous solutions to inverse problems in incompressible flow on numerous irregular geometries

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-18T23:36:54.613007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c7c637c0-bafe-4b9b-a875-25a4ea72da4a · inbound

Effects of fuel and soot concentrations on the inception and development of contrails cites this paper.

Effects of fuel and soot concentrations on the inception and development of contrails Physics-informed KAN PointNet: Deep learning for simultaneous solutions to inverse problems in incompressible flow on numerous irregular geometries

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-13T20:59:04.410769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f133ebbd-2574-431c-a462-044402b0cc89 · inbound

Making Gaussian Kolmogorov-Arnold Networks Reliable and Accurate cites this paper.

Making Gaussian Kolmogorov-Arnold Networks Reliable and Accurate Physics-informed KAN PointNet: Deep learning for simultaneous solutions to inverse problems in incompressible flow on numerous irregular geometries

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:51:07.172445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c996cb05-ffbd-4710-b26d-2d62f4f02737 · inbound

Partition-of-Unity Gaussian Kolmogorov-Arnold Networks cites this paper.

Partition-of-Unity Gaussian Kolmogorov-Arnold Networks Physics-informed KAN PointNet: Deep learning for simultaneous solutions to inverse problems in incompressible flow on numerous irregular geometries

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:36:13.123013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.