Paper Citation Record · LEDGER

A Survey on Optimal Transport for Machine Learning: Theory and Applications

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2106.01963.

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

pith.paper-citation-record.v1
2106.01963 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:19:44.201523Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T03:27:27.191907Z

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 68304f13-236b-4a05-b862-d85d62b85c6f · inbound

Enhancing Unsupervised Graph Few-shot Learning via Set Functions and Optimal Transport cites this paper.

Enhancing Unsupervised Graph Few-shot Learning via Set Functions and Optimal Transport A Survey on Optimal Transport for Machine Learning: Theory and Applications

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-10T21:19:44.201523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d062bc7-8048-4a00-92d0-fbda901ce116 · inbound

Constructing Cell-type Taxonomy by Optimal Transport with Relaxed Marginal Constraints cites this paper.

Constructing Cell-type Taxonomy by Optimal Transport with Relaxed Marginal Constraints A Survey on Optimal Transport for Machine Learning: Theory and Applications

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-10T04:31:56.121267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 301fb68a-482d-425c-a773-8bb9185f6ce2 · inbound

PINS: Proximal Iterations with Sparse Newton and Sinkhorn for Optimal Transport cites this paper.

PINS: Proximal Iterations with Sparse Newton and Sinkhorn for Optimal Transport A Survey on Optimal Transport for Machine Learning: Theory and Applications

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:27:27.193827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7e36de4f-fe84-447f-b1d8-2b60418dd28d · inbound

Geometry-Aware Decentralized Sinkhorn for Wasserstein Barycenters cites this paper.

Geometry-Aware Decentralized Sinkhorn for Wasserstein Barycenters A Survey on Optimal Transport for Machine Learning: Theory and Applications

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T23:10:44.719476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.