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Paper Citation Record · LEDGER

From probabilistic graphical models to generalized tensor networks for supervised learning

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1806.05964.

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

pith.paper-citation-record.v1
1806.05964 v2

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 2026-08-06T18:25:20.324971Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T06:36:00.928638Z

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 3c60b908-a3f9-41b6-88e2-920e20cb9688 · inbound

Advances in Machine Learning: Where Can Quantum Techniques Help? cites this paper.

Advances in Machine Learning: Where Can Quantum Techniques Help? From probabilistic graphical models to generalized tensor networks for supervised learning

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-06T18:25:20.324971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:25:20.324971Z digest=sha256:e0f942047eccc8c0285aeec6a43f90d2b417c86cacab78e5dff6d79604d3dbc0

Observation 1b333ab4-45cb-48cd-b793-e727b9a29c65 · inbound

Tensor-Augmented Convolutional Neural Networks: Enhancing Expressivity with Generic Tensor Kernels cites this paper.

Tensor-Augmented Convolutional Neural Networks: Enhancing Expressivity with Generic Tensor Kernels From probabilistic graphical models to generalized tensor networks for supervised learning

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:36:00.931326Z

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=2026-05-10T17:35:10.794244Z digest=sha256:570fcf8744ffba118b5f0eb0a4c4604b251e9e72bec7f7ada50af227347f429d