Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
How Implicit Regularization of ReLU Neural Networks Characterizes the Learned Function -- Part I: the 1-D Case of Two Layers with Random First Layer
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1911.02903.
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 2026-08-16T10:30:08.689978Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-24T05:06:00.381595Z
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 4def13e0-b6ba-40cf-92a1-5eacbbbdb3c9 · inbound
Universal approximation property of Banach space-valued random feature models including random neural networks cites this paper.
Universal approximation property of Banach space-valued random feature models including random neural networks How Implicit Regularization of ReLU Neural Networks Characterizes the Learned Function -- Part I: the 1-D Case of Two Layers with Random First Layer
Reference 41
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T05:06:00.385381Z
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 7c064db6-6c01-4510-83e2-93626671bc41 · inbound
Gradient Descent as a Shrinkage Operator for Spectral Bias cites this paper.
Gradient Descent as a Shrinkage Operator for Spectral Bias How Implicit Regularization of ReLU Neural Networks Characterizes the Learned Function -- Part I: the 1-D Case of Two Layers with Random First Layer
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:30:08.689978Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.