Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1708.02691.
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 2026-08-14T15:11:57.208703Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T00:47:30.807766Z
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 fee70d4e-034a-4446-85cd-d215469662dc · inbound
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness cites this paper.
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T15:45:59.661062Z
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 ead81ccd-72d9-4b21-a7f4-fe8f62c0f43a · inbound
Nonparametric Regression on Low-Dimensional Manifolds using Deep ReLU Networks : Function Approximation and Statistical Recovery cites this paper.
Nonparametric Regression on Low-Dimensional Manifolds using Deep ReLU Networks : Function Approximation and Statistical Recovery Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T15:11:57.208703Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 58e4f88d-fd94-4825-94e8-ff5bf30bdd3a · inbound
Training Optimus Prime, M.D.: Generating Medical Certification Items by Fine-Tuning OpenAI's gpt2 Transformer Model cites this paper.
Training Optimus Prime, M.D.: Generating Medical Certification Items by Fine-Tuning OpenAI's gpt2 Transformer Model Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T11:36:40.037460Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation faff3d9f-20c7-4a41-bcc2-2c92c3173cc4 · inbound
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators cites this paper.
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T03:17:25.366854Z
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 95d48016-bba6-49cb-88c1-8471e15fca47 · inbound
Deep neural network approximation theory for high-dimensional functions cites this paper.
Deep neural network approximation theory for high-dimensional functions Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations
Reference 51
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T12:39:29.122660Z
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 0a210c41-b5af-4248-b917-d9450c1fc6d2 · inbound
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models cites this paper.
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations
Reference 185
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-14T23:00:21.201381Z
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 91a41d86-68d8-4fd2-b994-0c8e04c46263 · inbound
A Theory on Flow Matching with Neural Networks cites this paper.
A Theory on Flow Matching with Neural Networks Universal Function Approximation by Deep Neural Nets with Bounded Width and ReLU Activations
Reference 211
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T00:47:30.809391Z
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.