Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Overview frequency principle/spectral bias in deep learning
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2201.07395.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T21:43:07.218426Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
23
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation a01524e5-c9e0-4660-8896-c4f8e47148a4 · inbound
Hipandas: Hyperspectral Image Joint Denoising and Super-Resolution by Image Fusion with the Panchromatic Image cites this paper.
Hipandas: Hyperspectral Image Joint Denoising and Super-Resolution by Image Fusion with the Panchromatic Image Overview frequency principle/spectral bias in deep learning
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T21:43:07.218426Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 930a79e4-b424-4b2e-bb5c-96b9dff60ed7 · inbound
The Unreasonable Effectiveness of Gaussian Score Approximation for Diffusion Models and its Applications cites this paper.
The Unreasonable Effectiveness of Gaussian Score Approximation for Diffusion Models and its Applications Overview frequency principle/spectral bias in deep learning
Reference 1950
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T16:54:56.833856Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 845178ee-5c24-4b8f-b89f-0b3abeff6451 · inbound
TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models cites this paper.
TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Overview frequency principle/spectral bias in deep learning
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T12:59:22.129996Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5aae15f6-afae-4b6f-b9e9-92b27511eb8d · inbound
On understanding and overcoming spectral biases of deep neural network learning methods for solving PDEs cites this paper.
On understanding and overcoming spectral biases of deep neural network learning methods for solving PDEs Overview frequency principle/spectral bias in deep learning
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T19:32:41.404863Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8678d070-4bcd-44ff-9ce1-5601a622a8b1 · inbound
Frequency Bias and OOD Generalization in Neural Operators under a Variable-Coefficient Wave Equation cites this paper.
Frequency Bias and OOD Generalization in Neural Operators under a Variable-Coefficient Wave Equation Overview frequency principle/spectral bias in deep learning
Reference 70
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T19:47:51.781443Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.