Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Better Approximations of High Dimensional Smooth Functions by Deep Neural Networks with Rectified Power Units
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1903.05858.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T14:09:59.969053Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-24T16:06:15.543657Z
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 4669c1f1-3330-49d9-90c2-4fc8cc3b38f3 · inbound
Space-time error estimates for deep neural network approximations for differential equations cites this paper.
Space-time error estimates for deep neural network approximations for differential equations Better Approximations of High Dimensional Smooth Functions by Deep Neural Networks with Rectified Power Units
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T14:09:59.969053Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 12d8aba0-e166-486d-bfff-5442b23854b8 · inbound
ChebNet: Efficient and Stable Constructions of Deep Neural Networks with Rectified Power Units via Chebyshev Approximations cites this paper.
ChebNet: Efficient and Stable Constructions of Deep Neural Networks with Rectified Power Units via Chebyshev Approximations Better Approximations of High Dimensional Smooth Functions by Deep Neural Networks with Rectified Power Units
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T16:06:15.547153Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 3dbab6ee-b973-4243-bb1c-10ffb4bb8985 · inbound
Distributional Off-Policy Evaluation with Deep Quantile Process Regression cites this paper.
Distributional Off-Policy Evaluation with Deep Quantile Process Regression Better Approximations of High Dimensional Smooth Functions by Deep Neural Networks with Rectified Power Units
Reference 71
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T12:06:03.946503Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.