Paper Citation Record · LEDGER

Classically Approximating Variational Quantum Machine Learning with Random Fourier Features

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2210.13200.

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

pith.paper-citation-record.v1
2210.13200 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:24:32.564867Z

measured 1 of 1 external citation measurements

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

5
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 79e8def4-c709-4cb1-8e9d-ac88cd45ca89 · inbound

Quantum Neural Networks for Cloud Cover Parameterizations in Climate Models cites this paper.

Quantum Neural Networks for Cloud Cover Parameterizations in Climate Models Classically Approximating Variational Quantum Machine Learning with Random Fourier Features

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T19:24:32.564867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f43905c3-91d5-4df0-9944-d2ca7946e572 · inbound

Out of Tune: Demystifying Noise-Effects on Quantum Fourier Models cites this paper.

Out of Tune: Demystifying Noise-Effects on Quantum Fourier Models Classically Approximating Variational Quantum Machine Learning with Random Fourier Features

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T04:53:36.495689Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fcb6404-9138-4c5e-952f-39d15ee74e92 · inbound

Photonic processor benchmarking for variational quantum process tomography cites this paper.

Photonic processor benchmarking for variational quantum process tomography Classically Approximating Variational Quantum Machine Learning with Random Fourier Features

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T18:24:51.541098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40a8edd6-126d-4f94-a534-3a3fdda86ac2 · inbound

Demonstration of Efficient Predictive Surrogates for Large-scale Quantum Processors cites this paper.

Demonstration of Efficient Predictive Surrogates for Large-scale Quantum Processors Classically Approximating Variational Quantum Machine Learning with Random Fourier Features

Reference 105

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:11.136457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abd3b2c8-5205-4c67-9823-c969b284ccfb · inbound

Artificial intelligence for representing and characterizing quantum systems cites this paper.

Artificial intelligence for representing and characterizing quantum systems Classically Approximating Variational Quantum Machine Learning with Random Fourier Features

Reference 156

Resolution: unresolved; no resolver link, observed 2026-08-05T05:50:39.339661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b58fec7b-45e3-4de4-823b-b2a49fe72e78 · inbound

Coherent-State Propagation: A Computational Framework for Simulating Bosonic Quantum Systems cites this paper.

Coherent-State Propagation: A Computational Framework for Simulating Bosonic Quantum Systems Classically Approximating Variational Quantum Machine Learning with Random Fourier Features

Reference 253

Resolution: verified exact; arxiv_id, observed 2026-05-10T03:29:21.794953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4fcfe76f-2d7f-478f-a9ec-69277b79bc8f · inbound

Beyond Gates: Pulse Level Quantum Fourier Models cites this paper.

Beyond Gates: Pulse Level Quantum Fourier Models Classically Approximating Variational Quantum Machine Learning with Random Fourier Features

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-08T20:24:09.304084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 73509177-4c2b-49d1-b485-4d4dfa2b4b60 · inbound

A Quantum-Classical Surrogate Model for the Collision Operator of the Lattice Boltzmann Method cites this paper.

A Quantum-Classical Surrogate Model for the Collision Operator of the Lattice Boltzmann Method Classically Approximating Variational Quantum Machine Learning with Random Fourier Features

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-07-01T05:45:25.800151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.