Paper Citation Record · LEDGER

Generalized Denoising Auto-Encoders as Generative Models

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1305.6663.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1305.6663 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T05:14:55.492219Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-07-04T12:19:50.233940Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
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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 aec8cb90-bbc2-4566-b9bb-80934d2dcd5c · inbound

Variational Sparse Paired Autoencoders (vsPAIR) for Inverse Problems and Uncertainty Quantification cites this paper.

Variational Sparse Paired Autoencoders (vsPAIR) for Inverse Problems and Uncertainty Quantification Generalized Denoising Auto-Encoders as Generative Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T05:14:55.492219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9e0b0f0-88a7-4dee-8480-a2cc40838f3a · inbound

Signal Decomposition Reveals Structure in Insider Threat Detection under Sparse Temporal Data cites this paper.

Signal Decomposition Reveals Structure in Insider Threat Detection under Sparse Temporal Data Generalized Denoising Auto-Encoders as Generative Models

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-05-16T02:37:10.360956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0ef31460-4ebf-47d1-8ad7-4974227af3fd · inbound

Closed form perturbative relativistic modifications to wave-packet dynamics in the quantum harmonic oscillator cites this paper.

Closed form perturbative relativistic modifications to wave-packet dynamics in the quantum harmonic oscillator Generalized Denoising Auto-Encoders as Generative Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-15T12:56:18.518533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6bb961c5-7f26-4962-b170-20987b0c95f2 · inbound

Constrained Variable Projection for Structured Problems cites this paper.

Constrained Variable Projection for Structured Problems Generalized Denoising Auto-Encoders as Generative Models

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-07-04T12:19:50.235354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1f71b2e3-5ef8-4f70-a4d0-883d9e5dd36b · inbound

Quantum Fourier Generative Models Trainable at Large Scale cites this paper.

Quantum Fourier Generative Models Trainable at Large Scale Generalized Denoising Auto-Encoders as Generative Models

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-07-01T15:25:48.692708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 09e42e86-ab2b-4177-862c-30a4b5582655 · inbound

Generating Bearing Vibration Signals at User-Specified Fault Probabilities Using PR-GAN and Counterfactual Methods cites this paper.

Generating Bearing Vibration Signals at User-Specified Fault Probabilities Using PR-GAN and Counterfactual Methods Generalized Denoising Auto-Encoders as Generative Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T13:22:00.688358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.