Paper Citation Record · LEDGER

A quantum algorithm to train neural networks using low-depth circuits

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1712.05304.

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

pith.paper-citation-record.v1
1712.05304 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T20:55:26.431592Z

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

85
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 57f086e3-99ec-4be0-abae-d9f85dc44c7e · inbound

PennyLane: Automatic differentiation of hybrid quantum-classical computations cites this paper.

PennyLane: Automatic differentiation of hybrid quantum-classical computations A quantum algorithm to train neural networks using low-depth circuits

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T15:14:44.127663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3715dc0e-f600-4f8a-b69c-565a872ef341 · inbound

Learning to learn with quantum neural networks via classical neural networks cites this paper.

Learning to learn with quantum neural networks via classical neural networks A quantum algorithm to train neural networks using low-depth circuits

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-24T23:00:03.232589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 85756700-f88a-45c0-a45f-9607a111b4d7 · inbound

Variational quantum thermalizers based on weakly-symmetric nonunitary multi-qubit operations cites this paper.

Variational quantum thermalizers based on weakly-symmetric nonunitary multi-qubit operations A quantum algorithm to train neural networks using low-depth circuits

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T20:55:26.431592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5149eb3-f601-4448-b1b4-1d5b203d3d64 · inbound

Scaling Quantum Algorithms via Dissipation: Avoiding Barren Plateaus cites this paper.

Scaling Quantum Algorithms via Dissipation: Avoiding Barren Plateaus A quantum algorithm to train neural networks using low-depth circuits

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T20:54:57.828844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55f1989c-5042-4535-a2b7-2384d1c8219e · inbound

A review of quantum machine learning and quantum-inspired applied methods to computational fluid dynamics cites this paper.

A review of quantum machine learning and quantum-inspired applied methods to computational fluid dynamics A quantum algorithm to train neural networks using low-depth circuits

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-18T06:42:26.349411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.