Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Deep ReLU network approximation of functions on a manifold
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1908.00695.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:27:01.986053Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T23:57:28.105803Z
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 bbf40dbd-aad1-46a3-8c2e-496f4ea26ce3 · inbound
Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights cites this paper.
Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights Deep ReLU network approximation of functions on a manifold
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T16:01:46.028034Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 3d3531f9-1893-40f3-9e42-00e8845c2814 · inbound
Weak Physics Informed Neural Networks for Geometry Compatible Hyperbolic Conservation Laws on Manifolds cites this paper.
Weak Physics Informed Neural Networks for Geometry Compatible Hyperbolic Conservation Laws on Manifolds Deep ReLU network approximation of functions on a manifold
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:27:01.986053Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b7745392-4dab-4895-ae1a-7f0552a7de47 · inbound
Understanding In-Context Learning on Structured Manifolds: Bridging Attention to Kernel Methods cites this paper.
Understanding In-Context Learning on Structured Manifolds: Bridging Attention to Kernel Methods Deep ReLU network approximation of functions on a manifold
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T00:40:51.745784Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 517efea0-6b01-4cc2-bbc0-06dadeabed0b · inbound
Phase Transition in Nonparametric Minimax Rates for Covariate Shifts on Approximate Manifolds cites this paper.
Phase Transition in Nonparametric Minimax Rates for Covariate Shifts on Approximate Manifolds Deep ReLU network approximation of functions on a manifold
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:19:15.453050Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fca51baf-0015-4f99-9521-56001d4c9882 · inbound
Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces cites this paper.
Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces Deep ReLU network approximation of functions on a manifold
Reference 100
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T13:21:59.297979Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4b20b56c-8174-46a5-98e9-f511c38c33f1 · inbound
A Composite Activation Function for Learning Stable Binary Representations cites this paper.
A Composite Activation Function for Learning Stable Binary Representations Deep ReLU network approximation of functions on a manifold
Reference 60
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:07:08.000306Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 4177bea0-64e7-4413-a911-2fa2a013ff40 · inbound
Generalization in Nonlinear Least Squares via Learned Feature Geometry cites this paper.
Generalization in Nonlinear Least Squares via Learned Feature Geometry Deep ReLU network approximation of functions on a manifold
Reference 76
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T23:57:28.107151Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.