Paper Citation Record · LEDGER

Gaussian Process Methods for Very Large Astrometric Data Sets

As of 21 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2507.10317.

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

pith.paper-citation-record.v1
2507.10317 v1

Coverage vector

measured 35 of 35 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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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 e7545ea5-cf10-44a8-ad4d-12e8cf6ea86c · outbound

This paper cites 2022, Astronomy & Astrophysics, 657, L12, 10.1051/0004-6361/202142465.

Gaussian Process Methods for Very Large Astrometric Data Sets 2022, Astronomy & Astrophysics, 657, L12, 10.1051/0004-6361/202142465

Reference 1

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This paper cites 2023, Astronomy & Astrophysics, 673, A115, 10.1051/0004-6361/202245518.

Gaussian Process Methods for Very Large Astrometric Data Sets 2023, Astronomy & Astrophysics, 673, A115, 10.1051/0004-6361/202245518

Reference 2

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Observation ecbd8437-450d-4b7b-9ddc-5d22f6be0148 · outbound

This paper cites an unresolved cited work.

Gaussian Process Methods for Very Large Astrometric Data Sets Unresolved cited work

Reference 3

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Observation e4259a59-18b4-4689-b379-a476b24a29a1 · outbound

This paper cites 2018, Monthly Notices of the Royal Astronomical Society, 482, 1417–1425, 10.1093/mnras/sty2813.

Gaussian Process Methods for Very Large Astrometric Data Sets 2018, Monthly Notices of the Royal Astronomical Society, 482, 1417–1425, 10.1093/mnras/sty2813

Reference 4

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This paper cites 2011, Galactic Dynamics: Second Edition (Princeton University Press), 10.2307/j.ctvc778ff.

Gaussian Process Methods for Very Large Astrometric Data Sets 2011, Galactic Dynamics: Second Edition (Princeton University Press), 10.2307/j.ctvc778ff

Reference 5

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This paper cites 2023, Astronomy & Astrophysics, 674, A7, 10.1051/0004-6361/202243685.

Gaussian Process Methods for Very Large Astrometric Data Sets 2023, Astronomy & Astrophysics, 674, A7, 10.1051/0004-6361/202243685

Reference 6

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Observation 82290010-3db3-46b6-a373-a477273d2843 · outbound

This paper cites 2015, The Astrophysical Journal Supplement Series, 216, 29, 10.1088/0067-0049/216/2/29.

Gaussian Process Methods for Very Large Astrometric Data Sets 2015, The Astrophysical Journal Supplement Series, 216, 29, 10.1088/0067-0049/216/2/29

Reference 7

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Observation 093e0f73-4d40-413d-8b61-89d77946047b · outbound

This paper cites 2013, The Astrophysical Journal, 779, 115, 10.1088/0004-637x/779/2/115.

Gaussian Process Methods for Very Large Astrometric Data Sets 2013, The Astrophysical Journal, 779, 115, 10.1088/0004-637x/779/2/115

Reference 8

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This paper cites 2023, Astronomy & Astrophysics, 674, A37, 10.1051/0004-6361/202243797.

Gaussian Process Methods for Very Large Astrometric Data Sets 2023, Astronomy & Astrophysics, 674, A37, 10.1051/0004-6361/202243797

Reference 9

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Observation 82c165d1-eaf0-410f-afe2-5ec86c048bd2 · outbound

This paper cites W., Rix, H.-W., & Ness, M.

Gaussian Process Methods for Very Large Astrometric Data Sets W., Rix, H.-W., & Ness, M

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:14.684334Z

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Observation 19cec49c-cfff-46d9-b04d-72e75eaf5f04 · outbound

This paper cites 2021, tinygp: The tiniest of Gaussian process libraries, 0.2.3.

Gaussian Process Methods for Very Large Astrometric Data Sets 2021, tinygp: The tiniest of Gaussian process libraries, 0.2.3

Reference 11

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Observation 429ece01-a01b-41a2-935a-5b922dd88c77 · outbound

This paper cites Iron Snails: non-equilibrium dynamics and spiral abundance patterns.

Gaussian Process Methods for Very Large Astrometric Data Sets Iron Snails: non-equilibrium dynamics and spiral abundance patterns

Reference 12

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Observation d5d94742-c7ce-4734-b6db-00d1a0ba8ea3 · outbound

This paper cites The Gaia mission.

Gaussian Process Methods for Very Large Astrometric Data Sets The Gaia mission

Reference 13

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Observation e8904d4f-5aa6-4fb3-9aff-5f9f1e5e2ba2 · outbound

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Gaussian Process Methods for Very Large Astrometric Data Sets Unresolved cited work

Reference 14

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Observation ce6c52ab-44b3-4af4-9451-1d220fd0ccc0 · outbound

This paper cites GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration.

Gaussian Process Methods for Very Large Astrometric Data Sets GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:14.715011Z

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Observation d68af127-408c-4324-a514-b21d95c651c0 · outbound

This paper cites 1997, in Advances in Neural Information Processing Systems 10 (NIPS 1997) (MIT Press), 493--499.

Gaussian Process Methods for Very Large Astrometric Data Sets 1997, in Advances in Neural Information Processing Systems 10 (NIPS 1997) (MIT Press), 493--499

Reference 16

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Observation 961de7f3-3b59-4a9e-b9c1-d9eed58113f4 · outbound

This paper cites 2022, The Astrophysical Journal, 936, 103, 10.3847/1538-4357/ac86cd.

Gaussian Process Methods for Very Large Astrometric Data Sets 2022, The Astrophysical Journal, 936, 103, 10.3847/1538-4357/ac86cd

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:14.728005Z

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Observation 240a6b4e-6e25-41fb-a6f1-3020db5f68dd · outbound

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Gaussian Process Methods for Very Large Astrometric Data Sets Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-06T17:42:15.563568Z

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Observation 01f352e3-5a1b-4366-afa5-f964da157181 · outbound

This paper cites 2015, in Proceedings of Machine Learning Research, Vol.

Gaussian Process Methods for Very Large Astrometric Data Sets 2015, in Proceedings of Machine Learning Research, Vol

Reference 19

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Observation 0a626c20-bf5f-4149-b3bb-d370834ba465 · outbound

This paper cites D., Blei, D.

Gaussian Process Methods for Very Large Astrometric Data Sets D., Blei, D

Reference 20

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Observation 7ab4f2ed-ce88-40ca-b18b-9096b6f92f45 · outbound

This paper cites 2018, Astronomy & Astrophysics, 616, A11, 10.1051/0004-6361/201832865.

Gaussian Process Methods for Very Large Astrometric Data Sets 2018, Astronomy & Astrophysics, 616, A11, 10.1051/0004-6361/201832865

Reference 21

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This paper cites 2023, Astronomy & Astrophysics, 674, A5, 10.1051/0004-6361/202244220.

Gaussian Process Methods for Very Large Astrometric Data Sets 2023, Astronomy & Astrophysics, 674, A5, 10.1051/0004-6361/202244220

Reference 22

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This paper cites 1989, , 239, 605, 10.1093/mnras/239.2.605.

Gaussian Process Methods for Very Large Astrometric Data Sets 1989, , 239, 605, 10.1093/mnras/239.2.605

Reference 23

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Observation e1f99b82-6e82-487b-ac18-feedb17e83a4 · outbound

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Gaussian Process Methods for Very Large Astrometric Data Sets Unresolved cited work

Reference 24

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Observation 65c9a57e-53f8-4c28-8b6f-cf1b90448088 · outbound

This paper cites Grid Search, Random Search, Genetic Algorithm: A Big Comparison for NAS.

Gaussian Process Methods for Very Large Astrometric Data Sets Grid Search, Random Search, Genetic Algorithm: A Big Comparison for NAS

Reference 25

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Gaussian Process Methods for Very Large Astrometric Data Sets Unresolved cited work

Reference 26

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Gaussian Process Methods for Very Large Astrometric Data Sets Unresolved cited work

Reference 27

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Observation 9c24bf5e-27ba-4a0c-80ad-9b3c1ba3cef3 · outbound

This paper cites 2007, in Advances in Neural Information Processing Systems, ed.

Gaussian Process Methods for Very Large Astrometric Data Sets 2007, in Advances in Neural Information Processing Systems, ed

Reference 28

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Observation fd9ad614-947a-427a-a6f3-c7ae319ef0b3 · outbound

This paper cites E., & Williams, C.

Gaussian Process Methods for Very Large Astrometric Data Sets E., & Williams, C

Reference 29

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Observation 594baf3b-f68b-44c0-b1ed-af94efa15784 · outbound

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Gaussian Process Methods for Very Large Astrometric Data Sets Unresolved cited work

Reference 30

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Observation ba4ff763-71e6-4c85-8b14-edcf252a5cf8 · outbound

This paper cites 2005, in Advances in Neural Information Processing Systems, ed.

Gaussian Process Methods for Very Large Astrometric Data Sets 2005, in Advances in Neural Information Processing Systems, ed

Reference 31

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This paper cites 2009, in Proceedings of Machine Learning Research, Vol.

Gaussian Process Methods for Very Large Astrometric Data Sets 2009, in Proceedings of Machine Learning Research, Vol

Reference 32

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Observation aa01a658-ddee-4359-a009-355738c837ec · outbound

This paper cites 2022, The Astrophysical Journal, 942, 12, 10.3847/1538-4357/aca27c.

Gaussian Process Methods for Very Large Astrometric Data Sets 2022, The Astrophysical Journal, 942, 12, 10.3847/1538-4357/aca27c

Reference 33

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Observation 643b1a9e-c7df-46be-b2b7-251c01c55d6c · outbound

This paper cites 2000, in Advances in Neural Information Processing Systems, ed.

Gaussian Process Methods for Very Large Astrometric Data Sets 2000, in Advances in Neural Information Processing Systems, ed

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:42:15.429743Z

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Observation ffa2dc34-14dd-4ff8-a77a-6184d94e1cf7 · outbound

This paper cites Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP).

Gaussian Process Methods for Very Large Astrometric Data Sets Kernel Interpolation for Scalable Structured Gaussian Processes (KISS-GP)

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T17:42:14.842809Z

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Pith citing papers

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