Pith. sign in

Paper Citation Record · LEDGER

Solving Partial Differential Equations with Point Source Based on Physics-Informed Neural Networks

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2111.01394.

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

pith.paper-citation-record.v1
2111.01394 v1

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 2026-08-12T06:34:41.77262+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:28:01.504616Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T10:58:03.002973Z

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 c659f605-f708-4abd-91f7-ab8c07b0abb2 · inbound

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction cites this paper.

A deep-learning model for predicting daily PM2.5 concentration in response to emission reduction Solving Partial Differential Equations with Point Source Based on Physics-Informed Neural Networks

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-06T23:28:01.504616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:28:01.504616Z digest=sha256:e9544f485948dd37b891d57edc629331b1e64b535284b42e7c6f3c25049a8201

Observation 2aa26686-f681-40cc-85f4-633583002791 · inbound

Physics-Informed Neural PDE Solvers via Spatio-Temporal MeanFlow cites this paper.

Physics-Informed Neural PDE Solvers via Spatio-Temporal MeanFlow Solving Partial Differential Equations with Point Source Based on Physics-Informed Neural Networks

Reference 54

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:51:28.330344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-12T03:54:07.625986Z digest=sha256:8e785ce69152814057e81519e5c113dd353bbe509334d06381b0f5fe2aeb5d3d

Observation 140db232-cb23-447a-831c-588bb3f063be · inbound

Physics-Informed Neural Networks and Radial Basis Functions for PDEs with Dirac Delta Sources cites this paper.

Physics-Informed Neural Networks and Radial Basis Functions for PDEs with Dirac Delta Sources Solving Partial Differential Equations with Point Source Based on Physics-Informed Neural Networks

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-03T10:58:03.005578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-27T09:46:27.863379Z digest=sha256:289a0f874e961ec08f9338b47366bff7375cdd8e1ede730e3a46637bb09370f6