Paper Citation Record · LEDGER

Inference, interference and invariance: How the Quantum Fourier Transform can help to learn from data

As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2409.00172.

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

pith.paper-citation-record.v1
2409.00172 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 2026-08-23T06:30:58.430688+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:35:11.891853Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T15:25:48.626210Z

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 ffed4157-5706-4e20-b837-a570eb1beb5c · inbound

The role of data-induced randomness in quantum machine learning classification tasks cites this paper.

The role of data-induced randomness in quantum machine learning classification tasks Inference, interference and invariance: How the Quantum Fourier Transform can help to learn from data

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T10:35:11.891853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c16d231-2d4d-4e9f-9e02-a626538f14c4 · inbound

Quantum entanglement provides a competitive advantage in adversarial games cites this paper.

Quantum entanglement provides a competitive advantage in adversarial games Inference, interference and invariance: How the Quantum Fourier Transform can help to learn from data

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-14T23:44:17.042117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12f1d47e-41be-4f22-849a-178c5703df6e · inbound

Spectral methods: crucial for machine learning, natural for quantum computers? cites this paper.

Spectral methods: crucial for machine learning, natural for quantum computers? Inference, interference and invariance: How the Quantum Fourier Transform can help to learn from data

Reference 104

Resolution: verified exact; arxiv_id, observed 2026-05-15T00:23:22.267074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation babc63d3-fe8f-429f-a4fb-8d893a12cf91 · inbound

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

Quantum Fourier Generative Models Trainable at Large Scale Inference, interference and invariance: How the Quantum Fourier Transform can help to learn from data

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-07-01T15:25:48.628350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.