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Paper Citation Record · LEDGER

Learning with a Wasserstein Loss

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1506.05439.

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

pith.paper-citation-record.v1
1506.05439 v3

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 2026-08-16T12:04:28.660364Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T13:57:48.308686Z

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 ba7ab420-1b81-4b6d-a199-f0791b19d353 · inbound

Collective Learning Mechanism based Optimal Transport Generative Adversarial Network for Non-parallel Voice Conversion cites this paper.

Collective Learning Mechanism based Optimal Transport Generative Adversarial Network for Non-parallel Voice Conversion Learning with a Wasserstein Loss

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-16T12:04:28.660364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:04:28.660364Z digest=sha256:86799a29ee32733a5404d6516fd66a0ef5981720f46acca6126bcb44fb99389f

Observation f2683a55-7e6e-403a-8fff-a42f5c709fc8 · inbound

Patch-Based 3D Variational Autoencoder for Super-Resolution of Turbulent Channel Flow cites this paper.

Patch-Based 3D Variational Autoencoder for Super-Resolution of Turbulent Channel Flow Learning with a Wasserstein Loss

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-06T13:57:48.313576Z

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=2026-08-06T13:57:48.282094Z digest=sha256:00101b744860c1c99c563d5ab90314ca2f1842ba4a1a08b5fa584913a6e9bfb2