Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
An Overview on Machine Learning Methods for Partial Differential Equations: from Physics Informed Neural Networks to Deep Operator Learning
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2408.13222.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T05:34:06.532978Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T00:04:06.954798Z
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 ad2564f4-d8aa-49aa-9728-80e1a61f246f · inbound
Optimal Convergence Rates for Neural Operators cites this paper.
Optimal Convergence Rates for Neural Operators An Overview on Machine Learning Methods for Partial Differential Equations: from Physics Informed Neural Networks to Deep Operator Learning
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T05:34:06.532978Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ff1a874e-2c88-4f88-b114-4e1721baf1b4 · inbound
Random Neural Network Expressivity for Non-Linear Partial Differential Equations cites this paper.
Random Neural Network Expressivity for Non-Linear Partial Differential Equations An Overview on Machine Learning Methods for Partial Differential Equations: from Physics Informed Neural Networks to Deep Operator Learning
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T00:04:06.956362Z
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.