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Paper Citation Record · LEDGER

A note on the relations between mixture models, maximum-likelihood and entropic optimal transport

As of 14 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 0 inbound Pith citation observations for arXiv:2501.12005.

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

pith.paper-citation-record.v1
2501.12005 v2

Coverage vector

measured 7 of 7 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:44:27.426108Z

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

7 of 7 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ac1ce43b-9597-455b-a6c7-b7c1f1e5f360 · outbound

This paper cites Entropic optimal transport is maximum-likelihood deconvolution.

A note on the relations between mixture models, maximum-likelihood and entropic optimal transport Entropic optimal transport is maximum-likelihood deconvolution

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:44:27.506917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T17:44:27.401858Z digest=sha256:7725a7e2fb62e72d7796eaf55b0c7c6fa61467309424af7e08e6153d77bf123a

Observation 2a596450-7fb3-4cfc-93c5-779d1169f185 · outbound

This paper cites Sinkhorn EM: An Expectation-Maximization algorithm based on entropic optimal transport.

A note on the relations between mixture models, maximum-likelihood and entropic optimal transport Sinkhorn EM: An Expectation-Maximization algorithm based on entropic optimal transport

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-10T17:44:27.405861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:44:27.405861Z digest=sha256:44f674b2c48986bf1274247491350238b287a336efa36661a8bde2eaa06b69ad

Observation 0c09397d-c75c-4879-8cf7-67d098c877e6 · outbound

This paper cites A unified framework for hard and soft clustering with regularized optimal transport.

A note on the relations between mixture models, maximum-likelihood and entropic optimal transport A unified framework for hard and soft clustering with regularized optimal transport

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-10T17:44:27.410645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:44:27.410645Z digest=sha256:968fb5158266be3b98408165433320941b6b5f0701a044ceb0abb42f03263bda

Observation 87f8dad9-425e-4f94-958c-a2c38d51e3d4 · outbound

This paper cites Computational optimal transport: With applications to data science.

A note on the relations between mixture models, maximum-likelihood and entropic optimal transport Computational optimal transport: With applications to data science

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-10T17:44:27.414540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:44:27.414540Z digest=sha256:ab8bfded5728dfe0e48f77ad119c553b2341bab4a079b6863792129d64613d0a

Observation 7b622ea4-1abd-4fc6-9425-6b141f4abc79 · outbound

This paper cites Sinkhorn distances: Lightspeed computation of optimal transport.

A note on the relations between mixture models, maximum-likelihood and entropic optimal transport Sinkhorn distances: Lightspeed computation of optimal transport

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:44:27.491325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T17:44:27.418605Z digest=sha256:e61d5082215209e6cb9eb66a0cf6fa5fa25005fcd78f025b201b753c6797f509

Observation 6a63ac2a-710f-4f4d-9df6-b3210338c745 · outbound

This paper cites Machine learning: a probabilistic perspective.

A note on the relations between mixture models, maximum-likelihood and entropic optimal transport Machine learning: a probabilistic perspective

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-10T17:44:27.422312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:44:27.422312Z digest=sha256:f652db6b9604a0aec964d51c7031cf401a50d4887ddf400fc3c46786f3f92555

Observation dae8a709-c9be-4c32-b0b2-6d45f59c5872 · outbound

This paper cites Courty, and Valentin Emyia.

A note on the relations between mixture models, maximum-likelihood and entropic optimal transport Courty, and Valentin Emyia

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:44:27.474853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-10T17:44:27.426108Z digest=sha256:e11b96e7eb9f961f4ed7eb7228c425cc9f77228d216a7a1c8430e83bfadd9d5c

Pith citing papers

No inbound Pith citation observations are available.