Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2311.12929.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T22:09:41.301817Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
0 of 0 outbound references displayed
External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
No outbound reference observations are available for this paper version.
Observation dca0c148-787c-4f16-b2ad-850cef93a66b · inbound
Quantum Machine Learning for State Tomography Using Classical Data Hierarchical Learning for Quantum ML: Novel Training Technique for Large-Scale Variational Quantum Circuits
Reference 112
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 9627e392-cddc-4532-87fa-bf4d94fc3647 · inbound
A Method for Constructing Quasi-Random Peaked Quantum Circuits Hierarchical Learning for Quantum ML: Novel Training Technique for Large-Scale Variational Quantum Circuits
Reference 13
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 184b8115-e1e0-4d76-92d1-c50adcab97d2 · inbound
Qvine: Vine Structured Quantum Circuits for Loading High Dimensional Distributions Hierarchical Learning for Quantum ML: Novel Training Technique for Large-Scale Variational Quantum Circuits
Reference 30
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation a647b0b0-d23e-4a34-a3ef-2cfa430c928a · inbound
Quantum Algorithm for Distributed Reduction of Entanglements (QADR): A Trainable and Simulation-Efficient QML Framework Hierarchical Learning for Quantum ML: Novel Training Technique for Large-Scale Variational Quantum Circuits
Reference 148
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.