Pith. sign in

Paper Citation Record · LEDGER

Quantum Machine Learning using Gaussian Processes with Performant Quantum Kernels

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2004.11280.

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

pith.paper-citation-record.v1
2004.11280 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:58:04.138898Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T15:24:50.055508Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 97a1a7f6-c9bd-4b60-8f12-b43fb739323d · inbound

A quantum inspired predictor of Parkinsons disease built on a diverse, multimodal dataset cites this paper.

A quantum inspired predictor of Parkinsons disease built on a diverse, multimodal dataset Quantum Machine Learning using Gaussian Processes with Performant Quantum Kernels

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-12T12:58:04.138898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:58:04.138898Z digest=sha256:33ad40a1f0dccf020ec856fd8b83a08319c9da3e39bf7af4bbf83b08f697ac0c

Observation 6c3e7988-5401-4556-9af4-3bc05ba70f3d · inbound

Hybrid Quantum-Classical Machine Learning Algorithms for Multi-Output Time-Series Forecasting at Utility Scale cites this paper.

Hybrid Quantum-Classical Machine Learning Algorithms for Multi-Output Time-Series Forecasting at Utility Scale Quantum Machine Learning using Gaussian Processes with Performant Quantum Kernels

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-06-30T15:24:50.056733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-30T15:20:26.328204Z digest=sha256:050bfd26c132c28b8cf5addb8d1812e7d1c4bb1ff6abcd71572b6e1b95692307