Paper Citation Record · LEDGER

Applying Topological Persistence in Convolutional Neural Network for Music Audio Signals

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1608.07373.

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

pith.paper-citation-record.v1
1608.07373 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T20:23:11.075919Z

measured 1 of 1 external citation measurements

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

Source: pith, 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

25
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 9a09a949-66cf-488b-be3e-c303a9adccc6 · inbound

The Good, The Efficient and the Inductive Biases: Exploring Efficiency in Deep Learning Through the Use of Inductive Biases cites this paper.

The Good, The Efficient and the Inductive Biases: Exploring Efficiency in Deep Learning Through the Use of Inductive Biases Applying Topological Persistence in Convolutional Neural Network for Music Audio Signals

Reference 232

Resolution: unresolved; no resolver link, observed 2026-08-12T20:23:11.075919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53ab4cb5-23e5-45a6-92f3-6abf96f6ada2 · inbound

Revisiting Point Cloud Completion: Are We Ready For The Real-World? cites this paper.

Revisiting Point Cloud Completion: Are We Ready For The Real-World? Applying Topological Persistence in Convolutional Neural Network for Music Audio Signals

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-12T12:06:02.908665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e9e0537-cd4e-48e6-a15e-abf06719dcf9 · inbound

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation cites this paper.

TopoLiDM: Topology-Aware LiDAR Diffusion Models for Interpretable and Realistic LiDAR Point Cloud Generation Applying Topological Persistence in Convolutional Neural Network for Music Audio Signals

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T11:42:22.844024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0fcbb48-3687-426f-aec0-9063f1870d5d · inbound

Information-Geometric Superposed Vowel Evaluation: Part 1. Moraic Syllabary (Japanese) cites this paper.

Information-Geometric Superposed Vowel Evaluation: Part 1. Moraic Syllabary (Japanese) Applying Topological Persistence in Convolutional Neural Network for Music Audio Signals

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-07-11T21:28:17.947209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.