Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Expressive power of tensor-network factorizations for probabilistic modeling, with applications from hidden Markov models to quantum machine learning
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1907.03741.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T10:39:19.113215Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T19:03:21.861271Z
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 71cdfaaa-c739-4722-a4cb-43a06986ae9a · inbound
Classical versus Quantum Models in Machine Learning: Insights from a Finance Application cites this paper.
Classical versus Quantum Models in Machine Learning: Insights from a Finance Application Expressive power of tensor-network factorizations for probabilistic modeling, with applications from hidden Markov models to quantum machine learning
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T10:39:19.113215Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d9b522d7-6254-4aaa-bab4-67ba1f28ae75 · inbound
Tensor decompositions on simplicial complexes with invariance cites this paper.
Tensor decompositions on simplicial complexes with invariance Expressive power of tensor-network factorizations for probabilistic modeling, with applications from hidden Markov models to quantum machine learning
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T05:17:49.738527Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 422b605d-91e8-471a-b2ad-2d23a6b38254 · inbound
The product structure of MPS-under-permutations cites this paper.
The product structure of MPS-under-permutations Expressive power of tensor-network factorizations for probabilistic modeling, with applications from hidden Markov models to quantum machine learning
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T19:03:21.864230Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.