Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Classically Approximating Variational Quantum Machine Learning with Random Fourier Features
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2210.13200.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T16:30:40.383485Z
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 439ad5be-cbc4-4e49-8e04-42b639ea447b · inbound
Quantum Machine Learning: A Hands-on Tutorial for Machine Learning Practitioners and Researchers cites this paper.
Quantum Machine Learning: A Hands-on Tutorial for Machine Learning Practitioners and Researchers Classically Approximating Variational Quantum Machine Learning with Random Fourier Features
Reference 264
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T16:30:40.383485Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+00:00.