Paper Citation Record · LEDGER

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows

As of 14 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 1 inbound Pith citation observation for arXiv:2505.22364.

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

pith.paper-citation-record.v1
2505.22364 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:16:01.709934Z

measured 19 of 19 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T11:29:23.064031Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

18 of 18 outbound references displayed

verified exact3
verified fuzzy2
unresolved12
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1f83af3b-fcff-40e4-9c86-58e747f99ad2 · outbound

This paper cites Density estimation using Real NVP.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows Density estimation using Real NVP

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:00.326333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3647fa58-6ab3-456e-8b77-b3a02b3b7a24 · outbound

This paper cites Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows Scalable Computations of Wasserstein Barycenter via Input Convex Neural Networks

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:16:02.294775Z

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.

Observation e455abdd-db6a-44a0-b743-067c00ecafad · outbound

This paper cites Projection to Fairness in Statistical Learning.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows Projection to Fairness in Statistical Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:00.629874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 849b254e-22f8-4322-b1b9-1f234dd1930a · outbound

This paper cites Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows Continuous Wasserstein-2 Barycenter Estimation without Minimax Optimization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:00.799723Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc7db5cf-6f90-4ba9-a152-7ef47e456f3b · outbound

This paper cites Large-Scale Optimal Transport via Adversarial Training with Cycle-Consistency.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows Large-Scale Optimal Transport via Adversarial Training with Cycle-Consistency

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:01.007085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3d7f889-5ac6-4d5f-97bc-be91f5105326 · outbound

This paper cites The Intrinsic Dimension of Images and Its Impact on Learning.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows The Intrinsic Dimension of Images and Its Impact on Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:01.365532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad91c5c1-64aa-45ea-8b3d-fd2f46b8a33c · outbound

This paper cites Auxiliary Results The following are some standard results from measure and integration theory that are used in this paper.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows Auxiliary Results The following are some standard results from measure and integration theory that are used in this paper

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:03.096101Z

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.

Observation 8333df36-709c-4b5a-9600-a77b6ef9160e · outbound

This paper cites an unresolved cited work.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows Unresolved cited work

Reference 18

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T13:16:02.760873Z

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.

Observation f4fa1a4d-35ee-4d63-9437-a07aced6281d · outbound

This paper cites Wasserstein Style Transfer.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows Wasserstein Style Transfer

Reference 1781

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:16:01.968613Z

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.

Observation 3041ad55-2f16-42ff-8066-43701d090b4d · outbound

This paper cites On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows

Reference 1982

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:00.412066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65c3ee87-ed1d-47a0-84a4-4689950a4150 · outbound

This paper cites Shen, J., Qu, Y ., Zhang, W., and Yu, Y.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows Shen, J., Qu, Y ., Zhang, W., and Yu, Y

Reference 2002

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:01.538638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa8a9ca5-3907-40d1-901e-ce16eee393a0 · outbound

This paper cites D., Bui, H., and Phung, D.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows D., Bui, H., and Phung, D

Reference 2014

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:03.343731Z

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.

Observation 35d2e243-b557-47ad-a2d2-2a319f30b61d · outbound

This paper cites Semi-Conditional Normalizing Flows for Semi-Supervised Learning.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows Semi-Conditional Normalizing Flows for Semi-Supervised Learning

Reference 2017

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:16:02.566624Z

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.

Observation 08c7aeac-8f0d-4efc-931a-ff8d24d75fa7 · outbound

This paper cites NICE: Non-linear Independent Components Estimation.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows NICE: Non-linear Independent Components Estimation

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:00.246171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63587cc5-733a-4eaf-b128-a4515e8373c5 · outbound

This paper cites On the regularization of Wasserstein GANs.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows On the regularization of Wasserstein GANs

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:01.202955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa8a1646-9eb6-4964-9c82-33565d05cd30 · outbound

This paper cites Adversarial Computation of Optimal Transport Maps.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows Adversarial Computation of Optimal Transport Maps

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:00.906523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f488c4a-69cc-456e-b8a1-90eaec7f0ad1 · outbound

This paper cites Wasserstein-2 Generative Networks.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows Wasserstein-2 Generative Networks

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:00.716265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89c07402-469f-43b1-8ef3-c1ccd7f9005a · outbound

This paper cites Verifying the Union of Manifolds Hypothesis for Image Data.

Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows Verifying the Union of Manifolds Hypothesis for Image Data

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:00.024867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 6997cbbc-8d3e-477c-bbd1-d33322fe8b73 · inbound

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation cites this paper.

Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation Computing Optimal Transport Maps and Wasserstein Barycenters Using Conditional Normalizing Flows

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T11:29:23.064031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.