Paper Citation Record · LEDGER

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning

As of 22 July 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2605.30375.

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

pith.paper-citation-record.v1
2605.30375 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T16:10:41.115543Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-22T06:31:00.163083+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

45 of 45 outbound references displayed

verified exact1
verified fuzzy0
unresolved41
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 57e244a2-1478-4835-b43b-01f4218b7bfc · outbound

This paper cites In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp

Reference 1

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Observation 64374220-da37-440f-9b38-2b088d4539ca · outbound

This paper cites Computational Mechanics64(2), 525–545 (2019).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Computational Mechanics64(2), 525–545 (2019)

Reference 2

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Observation 6b0ed785-8c5c-4974-ba21-46653fb165be · outbound

This paper cites DeepCFD: Efficient Steady-State Laminar Flow Approximation with Deep Convolutional Neural Networks.

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning DeepCFD: Efficient Steady-State Laminar Flow Approximation with Deep Convolutional Neural Networks

Reference 3

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Source-reported events for the cited work

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Observation 795fed44-9812-4afa-b976-b586ddce7c42 · outbound

This paper cites AIAA journal58(1), 25–36 (2020).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning AIAA journal58(1), 25–36 (2020)

Reference 4

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Observation 27791eeb-6f78-413f-b2b2-ca929fa6f3c2 · outbound

This paper cites Aiaa Journal57(3), 993–1003 (2019).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Aiaa Journal57(3), 993–1003 (2019)

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-29T16:10:41.115543Z

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Observation 12ff0b3d-4596-49b3-a7a7-6d564fd1094d · outbound

This paper cites In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-29T16:10:41.115543Z

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Observation 718ef0f3-1e74-4399-9cbd-aaea541e8a34 · outbound

This paper cites Advances in neural information processing systems32(2019).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Advances in neural information processing systems32(2019)

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-29T16:10:41.115543Z

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Observation b236504c-b00b-4fde-af54-144efc88c493 · outbound

This paper cites an unresolved cited work.

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Unresolved cited work

Reference 8

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Observation aecf21ca-7a64-4aa5-b91e-35e7b602f1d4 · outbound

This paper cites Journal of Computational Physics428, 110079 (2021) 23.

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Journal of Computational Physics428, 110079 (2021) 23

Reference 9

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Observation b8ded20d-f322-4c7b-b1fd-da73655a94de · outbound

This paper cites In: International Conference on Learning Representations (2020).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning In: International Conference on Learning Representations (2020)

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-29T16:10:41.115543Z

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Observation 2ac16bc0-c8bc-4969-9d21-4e78ba5d4b7a · outbound

This paper cites In: International Conference on Machine Learning, pp.

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning In: International Conference on Machine Learning, pp

Reference 11

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Observation f5c63359-7da8-447b-b522-b4f24977f9ec · outbound

This paper cites Physics of Fluids33(2) (2021).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Physics of Fluids33(2) (2021)

Reference 12

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Observation 23585fc9-8799-47d9-8210-677852af6b00 · outbound

This paper cites Engineering with Computers40(2), 1111–1126 (2024).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Engineering with Computers40(2), 1111–1126 (2024)

Reference 13

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Observation d71d9e18-4f79-49ad-8061-3588c41b85fd · outbound

This paper cites Advances in Neural Information Processing Systems35, 23463–23478 (2022).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Advances in Neural Information Processing Systems35, 23463–23478 (2022)

Reference 14

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Observation a8311079-7425-4ac6-951c-2b0e7c622791 · outbound

This paper cites Aiaa Journal60(9), 5249–5261 (2022).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Aiaa Journal60(9), 5249–5261 (2022)

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-29T16:10:41.115543Z

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Observation d363d0f9-74c7-4543-8b4a-189f6eba13e1 · outbound

This paper cites AIAA Journal60(7), 4413–4427 (2022).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning AIAA Journal60(7), 4413–4427 (2022)

Reference 16

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Observation aa38ef19-e88a-403e-b4c2-4fdbecb56afa · outbound

This paper cites Aerospace Science and Technology137, 108268 (2023).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Aerospace Science and Technology137, 108268 (2023)

Reference 17

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Observation ebd7899b-1644-4f29-981c-7104ef557590 · outbound

This paper cites Physics of Fluids35(10) (2023).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Physics of Fluids35(10) (2023)

Reference 18

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Observation 30be46ff-905d-4bb2-b2c4-ac1cb5129b47 · outbound

This paper cites Aerospace Science and Technology155, 109706 (2024).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Aerospace Science and Technology155, 109706 (2024)

Reference 19

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Observation 1a7f9869-70d6-4b16-be87-3a42122513ad · outbound

This paper cites Journal of Compu- tational Design and Engineering12(5), 175–189 (2025).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Journal of Compu- tational Design and Engineering12(5), 175–189 (2025)

Reference 20

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Observation f4e5a9f4-2ce9-4e54-8b9c-1a38ed2e9adb · outbound

This paper cites Scientific Reports14(1), 25496 (2024) 24.

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Scientific Reports14(1), 25496 (2024) 24

Reference 21

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Observation a7ecf0df-9309-4e4e-bd7d-4f05410df859 · outbound

This paper cites Communications Engineering4(1), 182 (2025).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Communications Engineering4(1), 182 (2025)

Reference 22

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Observation bd9e8a79-3d1a-4de2-8daa-6bd6248a8580 · outbound

This paper cites Physics of Fluids36(2) (2024).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Physics of Fluids36(2) (2024)

Reference 23

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Source-reported events for the cited work

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Observation 06732c2e-860a-4e00-a3dd-7f4a26f9ea98 · outbound

This paper cites Aerospace Science and Technology155, 109690 (2024).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Aerospace Science and Technology155, 109690 (2024)

Reference 24

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Observation 92e419f4-4e48-47b6-a39e-31a3165a122f · outbound

This paper cites Physics of Fluids37(8) (2025).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Physics of Fluids37(8) (2025)

Reference 25

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Observation 2fe3187f-9a6b-4cf0-88fd-6d711d6dc3c3 · outbound

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Aerospace Science and Technology159, 109991 (2025)

Reference 26

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Observation d16be2f6-dfe4-40ce-a87c-be45bc129ab7 · outbound

This paper cites Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences479(2275) (2023).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences479(2275) (2023)

Reference 27

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Observation 607b26c1-61c3-4872-aee4-abaed2858aa8 · outbound

This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning In: Proceedings of the AAAI Conference on Artificial Intelligence, vol

Reference 28

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Observation 186f3ad8-6b45-4805-a8b2-6399a06c76c4 · outbound

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Computer Methods in Applied Mechanics and Engineering443, 118022 (2025)

Reference 29

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Observation 9c21bb6e-4bbc-438c-ace0-8fd033622ab5 · outbound

This paper cites Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks.

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks

Reference 30

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Observation d6f2c76f-6738-4986-9053-aeb281ddeb8d · outbound

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Computer Methods in Applied Mechanics and Engineering384, 113938 (2021)

Reference 31

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Computers & Fluids284, 106440 (2024) 25

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning SIAM Journal on Scientific Computing43(5), 3055–3081 (2021)

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning SIAM, ??? (2011)

Reference 34

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Observation a110a993-6850-4ce3-8628-d184b320485f · outbound

This paper cites Mathe- matics of computation31(138), 333–390 (1977).

Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Mathe- matics of computation31(138), 333–390 (1977)

Reference 35

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Observation eb9ea3c4-9197-48e1-a971-d78f43cc4e8d · outbound

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Hierarchical Iterative Method in CFD Numerical Solution

Reference 36

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Observation 91438967-bb2a-4ad2-8b72-5f92506c5e9b · outbound

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning In: 42nd AIAA Aerospace Sciences Meeting and Exhibit, p

Reference 37

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Acta Aeronautica et Astronautica Sinica39(4), 021836 (2018)

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Acta Aeronautica et Astronautica Sinica39(7), 021997 (2018)

Reference 39

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Advances in neural information processing systems31(2018)

Reference 40

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 41

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework

Reference 42

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Advances in neural information processing systems30(2017)

Reference 43

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning Advances in neural information processing systems35, 23192–23204 (2022)

Reference 44

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Full-field prediction for engineering-scale three-dimensional aircraft with multigrid-hierarchical learning In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp

Reference 45

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Pith citing papers

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