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Paper Citation Record · LEDGER

Learning sufficient low-dimensional structures through conditional optimal transport

As of 7 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2607.18861.

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

pith.paper-citation-record.v1
2607.18861 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T14:15:03.263245Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

13 of 13 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c848dc3b-70db-4c6b-8db4-bad66a3c53b2 · outbound

This paper cites Since Φ(P(Y)) is Borel and W is G-measurable, the map fW is G-measurable.

Learning sufficient low-dimensional structures through conditional optimal transport Since Φ(P(Y)) is Borel and W is G-measurable, the map fW is G-measurable

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-01T14:15:03.140276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:15:03.140276Z digest=sha256:a7e8c06bcc7aaa600944273724ebf165d4d51e4f10685754e9464f3f7b08a3b8

Observation 22af8ed4-c60a-412d-9878-32001e31c24a · outbound

This paper cites cylindrical.

Learning sufficient low-dimensional structures through conditional optimal transport cylindrical

Reference 2

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unresolved
no resolver link, observed 2026-08-01T14:15:03.263245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:15:03.263245Z digest=sha256:f9d9dc052d8e2494aa993dc660c6ae6bef1a8d3c1dcab0805202e8720da73e75

Observation b14b6fa0-72a1-4d7d-b323-0c22970b6828 · outbound

This paper cites Since x7→K (x, Un) is measurable for every open Un, each set {x : K(x, Un) = 0 } is measurable.

Learning sufficient low-dimensional structures through conditional optimal transport Since x7→K (x, Un) is measurable for every open Un, each set {x : K(x, Un) = 0 } is measurable

Reference 10

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unresolved
no resolver link, observed 2026-08-01T14:15:03.058035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:15:03.058035Z digest=sha256:292eecf059156c8ec6b77b79f48dc21ca92d569a26644824425aff6b74609b92

Observation 31b1763b-63fe-4e2f-9ea9-c2f8ce2157ce · outbound

This paper cites stochastic dot product.

Learning sufficient low-dimensional structures through conditional optimal transport stochastic dot product

Reference 12

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unresolved
no resolver link, observed 2026-08-01T14:15:03.203333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:15:03.203333Z digest=sha256:d3da7f0b48a8bd870410c7b42b37a41d31253086cf1625edfc30f1fbab6df8ff

Observation 3f4b5fdf-cef0-4b52-b9dc-e85d85ff171c · outbound

This paper cites Springer, 2009.isbn: 978-3-540-71050-9.doi:10.1007/978-3-540-71050-9.

Learning sufficient low-dimensional structures through conditional optimal transport Springer, 2009.isbn: 978-3-540-71050-9.doi:10.1007/978-3-540-71050-9

Reference 338

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unresolved
no resolver link, observed 2026-08-01T14:15:02.990814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:15:02.990814Z digest=sha256:32c7ac144d57e5dd23703b0507fdb760490a40aab6eed9920d0cd6c2ea554bef

Observation 76c3d8ad-f3bc-4b2d-8b77-c2f2702052cf · outbound

This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

Learning sufficient low-dimensional structures through conditional optimal transport Fourier Neural Operator for Parametric Partial Differential Equations

Reference 904

Resolution
unresolved
no resolver link, observed 2026-08-01T14:15:02.771875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:15:02.771875Z digest=sha256:edc60006798de9c99143d02ffb33f43dd51ac08f5096893e4ad4132e647c9ab1

Observation ba5f0b2f-f070-4c5a-9c07-e086a1cf4f47 · outbound

This paper cites Improving and generalizing flow-based generative models with minibatch optimal transport.

Learning sufficient low-dimensional structures through conditional optimal transport Improving and generalizing flow-based generative models with minibatch optimal transport

Reference 1999

Resolution
unresolved
no resolver link, observed 2026-08-01T14:15:02.934085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:15:02.934085Z digest=sha256:442df7bfca0313930f97e0628f2ac5e17477a5eee77a79604370587d54d42a5f

Observation c09cc563-52d9-4988-92ee-3288a9fe00b8 · outbound

This paper cites Conditional Sampling with Monotone GANs: from Generative Models to Likelihood-Free Inference.

Learning sufficient low-dimensional structures through conditional optimal transport Conditional Sampling with Monotone GANs: from Generative Models to Likelihood-Free Inference

Reference 2005

Resolution
unresolved
no resolver link, observed 2026-08-01T14:15:02.533194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:15:02.533194Z digest=sha256:6aacde26b2362495597b0ac8275bab41905693d81664b2d4c5329f05a4fe473a

Observation 95f3bf5e-1193-472d-b305-9c8dc184b374 · outbound

This paper cites Invariant Feature Extraction Through Conditional Independence and the Optimal Transport Barycenter Problem: the Gaussian case.

Learning sufficient low-dimensional structures through conditional optimal transport Invariant Feature Extraction Through Conditional Independence and the Optimal Transport Barycenter Problem: the Gaussian case

Reference 2007

Resolution
verified exact
local_arxiv, observed 2026-08-01T14:18:42.025264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-01T14:15:02.628042Z digest=sha256:9ad0c16cb56fc63b164ddf7e678b3af070e90903a19b01684644939d14478b1a

Observation ea2bc749-4d56-44da-b22e-68e2f219e597 · outbound

This paper cites Functional Flow Matching.

Learning sufficient low-dimensional structures through conditional optimal transport Functional Flow Matching

Reference 2012

Resolution
unresolved
no resolver link, observed 2026-08-01T14:15:02.737232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:15:02.737232Z digest=sha256:7fa1a313b5aa9ab2a1dd3fbb6123bb3b47b9a361881f78c1b741233d399fccf9

Observation 1033acf8-9560-4916-a31b-c0f0e8ba680d · outbound

This paper cites Deep Dimension Reduction for Supervised Representation Learning.

Learning sufficient low-dimensional structures through conditional optimal transport Deep Dimension Reduction for Supervised Representation Learning

Reference 2015

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unresolved
no resolver link, observed 2026-08-01T14:15:02.684565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5bc6273d-aeb6-44e8-b3c3-a3773c8bc5a5 · outbound

This paper cites ‘On Flows Associated to Sobolev Vector Fields in Wiener Spaces: An Approach ` a la DiPerna–Lions’.

Learning sufficient low-dimensional structures through conditional optimal transport ‘On Flows Associated to Sobolev Vector Fields in Wiener Spaces: An Approach ` a la DiPerna–Lions’

Reference 2021

Resolution
verified exact
doi, observed 2026-08-01T14:18:42.634517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-01T14:15:02.466881Z digest=sha256:e952589d0cef2eb4e617e0715d77665cd0646a2e3e90a1114dc8581936e6fe86

Observation 60aba1c3-ef7c-4b44-933b-ee896234c14a · outbound

This paper cites The Monge optimal transport barycenter problem.

Learning sufficient low-dimensional structures through conditional optimal transport The Monge optimal transport barycenter problem

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-01T14:15:02.832043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T14:15:02.832043Z digest=sha256:9b3f0bc0a15593ba443375cc7efa70ca12b10170b3a0e6c37b7da0a8eba01f5f

Pith citing papers

No inbound Pith citation observations are available.