Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Exact and soft boundary conditions in Physics-Informed Neural Networks for the Variable Coefficient Poisson equation
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2310.02548.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T07:35:39.299956Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T11:41:30.277502Z
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 06e9b04c-ca9f-4174-ae0a-ee59a4b9f119 · inbound
A Wachspress-based transfinite formulation for exactly enforcing Dirichlet boundary conditions on convex polygonal domains in physics-informed neural networks cites this paper.
A Wachspress-based transfinite formulation for exactly enforcing Dirichlet boundary conditions on convex polygonal domains in physics-informed neural networks Exact and soft boundary conditions in Physics-Informed Neural Networks for the Variable Coefficient Poisson equation
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T11:41:30.279854Z
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 b4a3133a-7436-4994-869d-ea6404885482 · inbound
Approximating committor functions: Objective functions and training data sampling cites this paper.
Approximating committor functions: Objective functions and training data sampling Exact and soft boundary conditions in Physics-Informed Neural Networks for the Variable Coefficient Poisson equation
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T07:35:39.299956Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.