Paper Citation Record · LEDGER

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR

As of 12 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2505.17205.

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

pith.paper-citation-record.v1
2505.17205 v1

Coverage vector

measured 40 of 40 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

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External citation measurements

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Outbound references

Observation e0eec690-8cef-4c6b-b650-5ba06232502b · outbound

This paper cites Cosmic Concordance.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Cosmic Concordance

Reference 1

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Observation a4c113ee-e386-440d-85ea-2992b0662b7e · outbound

This paper cites Jimenez, The age of the universe (1997), arXiv:astro- ph/9701222 [astro-ph].

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Jimenez, The age of the universe (1997), arXiv:astro- ph/9701222 [astro-ph]

Reference 2

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Observation 90874329-254b-430c-bd1f-29ea8cb67951 · outbound

This paper cites Chaboyer, Physics Reports307, 23–30 (1998).

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Chaboyer, Physics Reports307, 23–30 (1998)

Reference 3

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This paper cites an unresolved cited work.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Unresolved cited work

Reference 4

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Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Unresolved cited work

Reference 5

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Observation 47e962b4-ebaa-4a30-8ceb-f7a482f079ff · outbound

This paper cites Jimenez and A.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Jimenez and A

Reference 6

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Observation 3cca22a3-e0ea-486f-8f82-f486088eda7c · outbound

This paper cites Simon, L.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Simon, L

Reference 7

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Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Unresolved cited work

Reference 8

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Observation a5786aaa-a72d-4954-83c2-9c615e753b7f · outbound

This paper cites Vagnozzi, F.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Vagnozzi, F

Reference 9

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Observation 70d633b9-84ea-466a-8651-f9efbaa52fd4 · outbound

This paper cites Wei and F.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Wei and F

Reference 10

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Observation 3328d6f2-d1f2-4415-8e86-5b9c6848bd15 · outbound

This paper cites Dantas, J.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Dantas, J

Reference 11

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This paper cites Dantas, J.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Dantas, J

Reference 12

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This paper cites Dantas, J.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Dantas, J

Reference 13

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Observation 2a7349af-f880-4f3c-9e77-fd9801c7d2b5 · outbound

This paper cites Capozziello, V.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Capozziello, V

Reference 14

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Observation 69e87940-352a-4e45-b127-f72e17e58f41 · outbound

This paper cites Pires, Z.-H.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Pires, Z.-H

Reference 15

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Observation 72df94e1-72b3-4ee2-8b7e-30f5a5bc6025 · outbound

This paper cites The Ages of the Oldest Astrophysical Objects in an Ellipsoidal Universe.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR The Ages of the Oldest Astrophysical Objects in an Ellipsoidal Universe

Reference 16

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Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Unresolved cited work

Reference 17

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Observation 5f041cfb-c061-43dc-8f5c-ef1dc80ec7de · outbound

This paper cites The age of extremely red and massive galaxies at very high redshift.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR The age of extremely red and massive galaxies at very high redshift

Reference 18

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Observation 7ab52821-9b43-4664-82ef-8e7aab475d5e · outbound

This paper cites Classification algorithms applied to structure formation simulations.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Classification algorithms applied to structure formation simulations

Reference 19

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Observation e37b8131-6b49-4d48-ba02-fe4faf92f7d0 · outbound

This paper cites Testing the $\Lambda$CDM paradigm with growth rate data and machine learning.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Testing the $\Lambda$CDM paradigm with growth rate data and machine learning

Reference 20

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Observation fa90be0c-4ff6-47dc-bd7b-426e4da86f81 · outbound

This paper cites Inferring galaxy dark halo properties from visible matter with Machine Learning.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Inferring galaxy dark halo properties from visible matter with Machine Learning

Reference 21

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Observation 2abb0899-51bf-49ef-bcaf-07367d205065 · outbound

This paper cites Measuring the Hubble Constant with cosmic chronometers: a machine learning approach.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Measuring the Hubble Constant with cosmic chronometers: a machine learning approach

Reference 22

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Observation bcbb9ae3-a9b2-44ea-877a-843d8e9cc152 · outbound

This paper cites ParamANN: A Neural Network to Estimate Cosmological Parameters for $\Lambda$CDM Universe Using Hubble Measurements.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR ParamANN: A Neural Network to Estimate Cosmological Parameters for $\Lambda$CDM Universe Using Hubble Measurements

Reference 23

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Observation 0c1c0efe-209f-48da-b721-ed8ab6831579 · outbound

This paper cites A New $\sim 5\sigma$ Tension at Characteristic Redshift from DESI-DR1 BAO and DES-SN5YR Observations.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR A New $\sim 5\sigma$ Tension at Characteristic Redshift from DESI-DR1 BAO and DES-SN5YR Observations

Reference 24

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Observation 5b219742-eb6e-4ee6-9fb1-e297a443dd56 · outbound

This paper cites Bounded Dark Energy.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Bounded Dark Energy

Reference 25

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Observation 24865b1f-a6e2-4d3e-9368-6b21be0c744a · outbound

This paper cites Metropoliset al., Los Alamos Science15, 125 (1987).

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Metropoliset al., Los Alamos Science15, 125 (1987)

Reference 26

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Observation 02678352-508a-471c-b828-f8711141db18 · outbound

This paper cites Sandage, Annual Review of Astron and Astrophys26, 561 (1988).

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Sandage, Annual Review of Astron and Astrophys26, 561 (1988)

Reference 27

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Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Unresolved cited work

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This paper cites Savage, N.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Savage, N

Reference 29

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This paper cites Doran, S.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Doran, S

Reference 30

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This paper cites Komatsu, J.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Komatsu, J

Reference 31

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Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Unresolved cited work

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Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Unresolved cited work

Reference 33

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This paper cites Planck Collaboration, Aghanim, Y.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Planck Collaboration, Aghanim, Y

Reference 34

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This paper cites Kosowsky, New Astronomy Reviews47, 939 (2003).

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Kosowsky, New Astronomy Reviews47, 939 (2003)

Reference 35

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This paper cites Stobie, J.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Stobie, J

Reference 36

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This paper cites Foreman-Mackey, D.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Foreman-Mackey, D

Reference 37

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Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR Unresolved cited work

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This paper cites The Age of the Universe with Globular Clusters III: Gaia distances and hierarchical modeling.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR The Age of the Universe with Globular Clusters III: Gaia distances and hierarchical modeling

Reference 39

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This paper cites The results demonstrated that the SVR technique performed the best, accurately capturing the nonlinear behavior of the data while avoiding overfitting.

Reconstructing Cosmic History with Machine Learning: A Study Using CART, MLPR, and SVR The results demonstrated that the SVR technique performed the best, accurately capturing the nonlinear behavior of the data while avoiding overfitting

Reference 6680

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Pith citing papers

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