Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
PySINDy: A comprehensive Python package for robust sparse system identification
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2111.08481.
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 2026-08-15T16:37:34.329147Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T14:44:45.449081Z
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 20ed31af-612f-484c-9cc4-957d7e60c5a6 · inbound
Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models cites this paper.
Knowledge Integration for Physics-informed Symbolic Regression Using Pre-trained Large Language Models PySINDy: A comprehensive Python package for robust sparse system identification
Reference 75
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T16:37:34.329147Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3681d175-d9bb-400c-9089-debb9c6b6827 · inbound
Physics-based Digital Twins for Integrated Thermal Energy Systems Using Active Learning cites this paper.
Physics-based Digital Twins for Integrated Thermal Energy Systems Using Active Learning PySINDy: A comprehensive Python package for robust sparse system identification
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T04:05:58.197533Z
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 80ed94a5-c6bc-4e9e-9477-df88341be515 · inbound
Multi-Fidelity Learning with Shallow Recurrent Decoders for Multi-Physics Applications cites this paper.
Multi-Fidelity Learning with Shallow Recurrent Decoders for Multi-Physics Applications PySINDy: A comprehensive Python package for robust sparse system identification
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T14:44:45.450851Z
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.