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Paper Citation Record · LEDGER

Transport information geometry I: Riemannian calculus on probability simplex

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1803.06360.

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

pith.paper-citation-record.v1
1803.06360 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:23:20.062444Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T13:23:27.076732Z

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 6f7b29a9-900e-428f-a829-dbd31f657c8a · inbound

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation cites this paper.

On the Transferability and Discriminability of Repersentation Learning in Unsupervised Domain Adaptation Transport information geometry I: Riemannian calculus on probability simplex

Reference 60

Resolution
verified exact
local_arxiv, observed 2026-08-07T13:23:27.193282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:23:20.062444Z digest=sha256:75135a9d691f12c6f8c3351f5cf5a60ec6501a3d8a31693d976945f8f93eb69e

Observation 92f9c7d8-f42f-4ed2-908b-1778d50adc5f · inbound

A kernel method for the learning of Wasserstein geometric flows cites this paper.

A kernel method for the learning of Wasserstein geometric flows Transport information geometry I: Riemannian calculus on probability simplex

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-04T06:54:31.275829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T06:54:31.275829Z digest=sha256:e1b13eb52f899b185939182acba99a0ed67b017e812c7a5d96ddb93f656c3f89