Paper Citation Record · LEDGER

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications

As of 21 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2412.00286.

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

pith.paper-citation-record.v1
2412.00286 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:36:58.829007Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

verified exact0
verified fuzzy10
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 745178fa-d9a6-46a0-9f0a-da12c566c2e6 · outbound

This paper cites Quantum computing in the nisq era and beyond.

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications Quantum computing in the nisq era and beyond

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:36:59.099713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9de0f28d-3aab-4e6f-93e2-6e033594f7e1 · outbound

This paper cites Supervised quantum machine learning models are kernel methods.

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications Supervised quantum machine learning models are kernel methods

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T05:36:58.760680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 899f617a-1d46-4f95-845e-feb412128a46 · outbound

This paper cites Quantum embeddings for machine learning, 2020.

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications Quantum embeddings for machine learning, 2020

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:36:59.084760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cd375bca-5c16-4d45-83f8-a156c4b15762 · outbound

This paper cites Invited: Trainable discrete feature embeddings for quantum machine learning.

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications Invited: Trainable discrete feature embeddings for quantum machine learning

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:36:59.069289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cecbc7ba-37f7-49c9-bd01-298fa9640460 · outbound

This paper cites Simulating a perceptron on a quantum computer.

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications Simulating a perceptron on a quantum computer

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:36:59.054165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 11582061-9126-457c-b0a8-f50dab515f8b · outbound

This paper cites Genetic algorithms.

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications Genetic algorithms

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:36:59.038657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation e1214d47-33da-4e48-96ed-93f661378857 · outbound

This paper cites Doriguello and Ashley Montanaro.

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications Doriguello and Ashley Montanaro

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:36:59.022572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a6ef2b7d-cd35-435f-a428-47fc03c5eaa4 · outbound

This paper cites an unresolved cited work.

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-12T05:36:59.004080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7823660b-8fc8-4665-9f8f-8accd530e7d8 · outbound

This paper cites Automatic and effective discovery of quantum kernels, 2023.

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications Automatic and effective discovery of quantum kernels, 2023

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:36:58.981387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6d9e75bf-af8a-4b6a-86ee-8aacea54995e · outbound

This paper cites Emre Sahin, Benjamin C.

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications Emre Sahin, Benjamin C

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:36:58.964666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation affcfaf8-2948-4668-8261-ef0ec51d5098 · outbound

This paper cites Circuit-centric quantum classifiers.

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications Circuit-centric quantum classifiers

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:36:58.947255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2f47764f-7c61-40c5-8ba6-61dad3b15f4f · outbound

This paper cites Finding groups in data: an introduction to cluster analysis.

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications Finding groups in data: an introduction to cluster analysis

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:36:58.929860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 55fec3d4-b0e5-43de-8092-d7bbd698695c · outbound

This paper cites an unresolved cited work.

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-12T05:36:58.912712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c0a9d274-cbe0-4725-b381-f468166a657c · outbound

This paper cites Tiny imagenet visual recognition challenge.

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications Tiny imagenet visual recognition challenge

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T05:36:58.823984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5501bff-d8ad-44e4-852a-8abc64c10a4d · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Optimizing Quantum Embedding using Genetic Algorithm for QML Applications UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T05:36:58.829007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.