Paper Citation Record · LEDGER

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures

As of 8 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2506.23615.

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

pith.paper-citation-record.v1
2506.23615 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:41:38.035306Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

39 of 39 outbound references displayed

verified exact6
verified fuzzy5
unresolved20
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bfa9a9c9-d21a-44b1-80c9-c45f342b76a0 · outbound

This paper cites Skomski, J.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Skomski, J

Reference 1

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Observation fcce36e0-abff-4c83-8392-4e6aa53fa4db · outbound

This paper cites Poudyal, J.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Poudyal, J

Reference 2

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Observation 1d6c37b4-978b-40a0-a313-237c118e5f1c · outbound

This paper cites Sanchez-Gonzalez, J.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Sanchez-Gonzalez, J

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:41:41.391358Z

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This paper cites an unresolved cited work.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Unresolved cited work

Reference 4

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Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Unresolved cited work

Reference 5

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Observation d32d4a66-0388-44a5-9dd7-4910af5eb153 · outbound

This paper cites an unresolved cited work.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Unresolved cited work

Reference 6

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Observation 370dd6e5-2ba3-4b58-9878-43ecfd853168 · outbound

This paper cites Hamilton, Z.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Hamilton, Z

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:41:41.218550Z

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Observation 1f799c8d-b86b-49bb-900b-a0ba730ec1bb · outbound

This paper cites Paszke, S.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Paszke, S

Reference 8

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Observation a0d7ced0-7af2-45e4-8c50-e55dd99d3ffd · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Fast Graph Representation Learning with PyTorch Geometric

Reference 9

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This paper cites an unresolved cited work.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Unresolved cited work

Reference 10

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Source-reported events for the cited work

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Observation 744de8a0-df0e-496b-969b-cfc177692cf9 · outbound

This paper cites an unresolved cited work.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Unresolved cited work

Reference 11

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Source-reported events for the cited work

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Observation 0c3c2d41-d2b1-43e4-906a-f43c3c53790a · outbound

This paper cites Moustafa, A.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Moustafa, A

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T21:41:36.184277Z

Source-reported events for the cited work

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Observation 4ea7d172-c06b-4d83-9781-fb50ccaf8eb3 · outbound

This paper cites Singh, D.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Singh, D

Reference 13

Resolution: verified exact; doi, observed 2026-08-06T21:41:38.976342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation eb7b203b-cd7b-4560-a6e6-a69f0f0d75f5 · outbound

This paper cites an unresolved cited work.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Unresolved cited work

Reference 14

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Source-reported events for the cited work

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Observation 6b764054-fc61-48df-b34c-dcbb8e7a2ed4 · outbound

This paper cites Marsaglia, Choosing a Point from the Surface of a Sphere, The Annals of Mathematical Statistics 43 (2) (1972) 645–646.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Marsaglia, Choosing a Point from the Surface of a Sphere, The Annals of Mathematical Statistics 43 (2) (1972) 645–646

Reference 15

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Source-reported events for the cited work

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Observation 9170b2d4-68fa-41a9-96e8-7fedb6b06368 · outbound

This paper cites an unresolved cited work.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Unresolved cited work

Reference 16

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Source-reported events for the cited work

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Observation 1d7474a2-9271-4548-a2b7-8e7e78644551 · outbound

This paper cites Pedregosa, G.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Pedregosa, G

Reference 17

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Observation 37dfab0e-ca6e-4135-9c4e-d510cee9711c · outbound

This paper cites Permutation feature importance.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Permutation feature importance

Reference 18

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Source-reported events for the cited work

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Observation 5ef550a5-d5c7-4cf7-8b54-814d058a8309 · outbound

This paper cites Improving neural networks by preventing co-adaptation of feature detectors.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Improving neural networks by preventing co-adaptation of feature detectors

Reference 19

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Source-reported events for the cited work

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Observation 3eaa564e-98ea-46f9-8155-82cdfe29758a · outbound

This paper cites an unresolved cited work.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Unresolved cited work

Reference 20

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Observation 74e2bc6a-dfe2-4ac2-8326-7fee9a6e2c18 · outbound

This paper cites Decoupled Weight Decay Regularization.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Decoupled Weight Decay Regularization

Reference 21

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Observation 1b730ced-8df8-4db3-8c4a-bc1ae6ae95c5 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Adam: A Method for Stochastic Optimization

Reference 22

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Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Unresolved cited work

Reference 23

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This paper cites an unresolved cited work.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Unresolved cited work

Reference 24

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Source-reported events for the cited work

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Observation a472e81a-27f6-4667-9c1e-a440b5fb5a55 · outbound

This paper cites Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Graph Neural Network Training Systems: A Performance Comparison of Full-Graph and Mini-Batch

Reference 25

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Source-reported events for the cited work

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Observation 00c6ebc7-cab2-4965-bd22-02f2f1810e72 · outbound

This paper cites an unresolved cited work.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Unresolved cited work

Reference 26

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Source-reported events for the cited work

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Observation d75c437b-3c69-4b2b-9ab8-a5287e903534 · outbound

This paper cites Broadwater, Graph Neural Networks in Action, Manning Publica- tions, US, 2025, oCLC: 1482783825.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Broadwater, Graph Neural Networks in Action, Manning Publica- tions, US, 2025, oCLC: 1482783825

Reference 27

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Observation 47f501fb-2301-470c-b42e-3d1db2172ffb · outbound

This paper cites Adding Gradient Noise Improves Learning for Very Deep Networks.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Adding Gradient Noise Improves Learning for Very Deep Networks

Reference 28

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Observation 97c6cc76-851a-4241-867b-269d85e9cd66 · outbound

This paper cites Gawlikowski, C.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Gawlikowski, C

Reference 29

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Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Unresolved cited work

Reference 30

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Observation df530a49-ba7c-4d1d-8c7d-25b88cece052 · outbound

This paper cites What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?

Reference 31

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This paper cites an unresolved cited work.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Unresolved cited work

Reference 32

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Observation 33751b59-ea64-4504-9820-16e210273738 · outbound

This paper cites an unresolved cited work.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Unresolved cited work

Reference 33

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Source-reported events for the cited work

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Observation af80ef4d-875f-4902-af12-5d53139c48d1 · outbound

This paper cites Confidence curves for UQ validation: probabilistic reference vs. oracle.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Confidence curves for UQ validation: probabilistic reference vs. oracle

Reference 34

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Observation 0c8878e1-f9a4-4f7a-9502-eab1595c0fda · outbound

This paper cites Project, Magnetic materials ontology, https://github.com/ MaMMoS-project/MagneticMaterialsOntology, accessed: 2025-05-21 (2024).

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Project, Magnetic materials ontology, https://github.com/ MaMMoS-project/MagneticMaterialsOntology, accessed: 2025-05-21 (2024)

Reference 35

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Observation ae2e014b-df9a-40da-a462-a8e9beeb309d · outbound

This paper cites an unresolved cited work.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Unresolved cited work

Reference 36

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Observation e5eb3463-43e3-44f0-89e7-9c53d769507b · outbound

This paper cites Out-Of-Distribution Generalization on Graphs: A Survey.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Out-Of-Distribution Generalization on Graphs: A Survey

Reference 37

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Observation 02ebd4ed-3a04-4aee-b6c7-368d4d88f7f4 · outbound

This paper cites Bance, B.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Bance, B

Reference 38

Resolution: malformed identifier; no resolver link, observed 2026-08-06T21:41:37.948489Z

Source-reported events for the cited work

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Observation 87aa7b3b-97eb-43d0-99da-b339b0f112c8 · outbound

This paper cites Kovacs, J.

Graph Neural Networks to Predict Coercivity of Hard Magnetic Microstructures Kovacs, J

Reference 39

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Source-reported events for the cited work

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Pith citing papers

No inbound Pith citation observations are available.