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Paper Citation Record · LEDGER

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds

As of 10 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2502.03439.

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

pith.paper-citation-record.v1
2502.03439 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T04:49:30.324855Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

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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

35 of 35 outbound references displayed

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External citation measurements

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Outbound references

Observation 87aecbf7-ed5f-4655-810f-074c39585b68 · outbound

This paper cites Learning representations and generative models for 3d point clouds, 2018.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Learning representations and generative models for 3d point clouds, 2018

Reference 1

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Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Unresolved cited work

Reference 2

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Observation 26dbd91c-95cf-4212-9fdd-0f1e8b4267df · outbound

This paper cites A User’s Guide to Optimal Transport, pages 1–155.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds A User’s Guide to Optimal Transport, pages 1–155

Reference 3

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Observation 12fede98-333c-4f2a-bbfa-1cb1e26ee19e · outbound

This paper cites Wasserstein generative adversarial networks.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Wasserstein generative adversarial networks

Reference 4

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Observation 460e75b9-5111-4f8b-b534-10d7f9973d52 · outbound

This paper cites Boyer, Yonatan Lipman, Elizabeth M.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Boyer, Yonatan Lipman, Elizabeth M

Reference 5

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Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Unresolved cited work

Reference 6

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Observation 2015f0c7-1431-44bf-8458-9a6cbc42c4ec · outbound

This paper cites Approximating persistent homology for large datasets, 2022.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Approximating persistent homology for large datasets, 2022

Reference 7

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Observation 5c73af06-a1f3-4c54-8c30-e168f9bd91fe · outbound

This paper cites Kung, Prabhjot Mundi, Joseph O.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Kung, Prabhjot Mundi, Joseph O

Reference 8

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Observation 92f19a2a-599a-4afe-9db3-3d250f127f21 · outbound

This paper cites Linearized wasserstein dimen- sionality reduction with approximation guarantees, 2023.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Linearized wasserstein dimen- sionality reduction with approximation guarantees, 2023

Reference 9

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Observation 7df131f4-ccfc-4744-a779-4f5e5be4e890 · outbound

This paper cites Rates of estimation of optimal transport maps using plug-in estimators via barycentric projections.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Rates of estimation of optimal transport maps using plug-in estimators via barycentric projections

Reference 10

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Observation 8fbb4788-df16-4300-ad09-12b81e99816b · outbound

This paper cites The diffusion geometry of fibre bundles: Horizontal diffusion maps.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds The diffusion geometry of fibre bundles: Horizontal diffusion maps

Reference 11

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Observation 60a00a07-f5cd-4f24-83ff-948afdd7e4b6 · outbound

This paper cites On Hölder continuity-in-time of the optimal transport map towards measures along a curve.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds On Hölder continuity-in-time of the optimal transport map towards measures along a curve

Reference 12

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Observation 7ba367ee-29a9-4f6d-bcc2-9301b1f07c58 · outbound

This paper cites Supervised learning of sheared distributions using linearized optimal transport.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Supervised learning of sheared distributions using linearized optimal transport

Reference 13

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Observation 48f7e1fc-f63d-4708-aa80-0240bcbaf7db · outbound

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Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Unresolved cited work

Reference 14

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Observation b5a463be-9aab-482e-b86f-e11f94b91ca3 · outbound

This paper cites Kevrekidis, Joseph O.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Kevrekidis, Joseph O

Reference 15

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Observation c6331501-be5a-4ecf-a852-1a28661ec69f · outbound

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Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Unresolved cited work

Reference 16

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Observation d0e3ae75-26b3-49ac-867e-bc9fed47fdb5 · outbound

This paper cites Quantitative stability of optimal transport maps and linearization of the 2-Wasserstein space.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Quantitative stability of optimal transport maps and linearization of the 2-Wasserstein space

Reference 17

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Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Linear Optimal Transport Embedding: Provable Wasserstein classification for certain rigid transformations and perturbations

Reference 18

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This paper cites The geometry of dissipative evolution equations: The porus medium equation.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds The geometry of dissipative evolution equations: The porus medium equation

Reference 19

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Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Unresolved cited work

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Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Computational optimal transport

Reference 21

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Observation d730c8cc-d31f-4033-bbf4-cc2b582e02d5 · outbound

This paper cites Entropic estimation of optimal transport maps.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Entropic estimation of optimal transport maps

Reference 22

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This paper cites Qi, Hao Su, Kaichun Mo, and Leonidas J.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Qi, Hao Su, Kaichun Mo, and Leonidas J

Reference 23

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Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Qi, Li Yi, Hao Su, and Leonidas J

Reference 24

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This paper cites On a generalization of wasserstein distance and the beckmann problem to connection graphs, 2024.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds On a generalization of wasserstein distance and the beckmann problem to connection graphs, 2024

Reference 25

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This paper cites The earth mover’s distance as a metric for image retrieval.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds The earth mover’s distance as a metric for image retrieval

Reference 26

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Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Wasserstein propagation for semi- supervised learning

Reference 27

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Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds St Clair and Doug M

Reference 28

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Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Unresolved cited work

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Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Optimal Transport: Old and New, volume 338

Reference 30

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Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Ozolek, and Gustavo K

Reference 31

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This paper cites Sarma, Michael M.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Sarma, Michael M

Reference 32

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Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Unresolved cited work

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Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Deep sets

Reference 34

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This paper cites Understanding bag-of-words model: a statistical framework.

Linearized Optimal Transport pyLOT Library: A Toolkit for Machine Learning on Point Clouds Understanding bag-of-words model: a statistical framework

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T04:49:30.369448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-09T04:49:30.324855Z digest=sha256:6efeac7181167ff61664976b9fd9f18a4ed42b6c165176b0ebabec97db4f009d

Pith citing papers

No inbound Pith citation observations are available.