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Paper Citation Record · LEDGER

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements

As of 18 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 0 inbound Pith citation observations for arXiv:2411.17433.

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

pith.paper-citation-record.v1
2411.17433 v1

Coverage vector

measured 69 of 69 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:12:25.513677Z

measured 69 of 69 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

69 of 69 outbound references displayed

  • verified exact5
  • verified fuzzy40
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6bb94be8-b00c-4a14-8170-a3868e8cc64a · outbound

This paper cites Mortensen, H.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Mortensen, H

Reference 1

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verified fuzzy
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Source-reported events for the cited work

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Observation 29fe2bee-f9e1-42cf-a019-5d5644201e6d · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation d9f54026-202a-4003-af02-dfdc580a6283 · outbound

This paper cites Abad ´ ıa-Heredia, M.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Abad ´ ıa-Heredia, M

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 1a5818d5-4f36-4e89-a8d9-1907b223adfc · outbound

This paper cites A predictive physics-aware hybrid reduced order model for reacting flows.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements A predictive physics-aware hybrid reduced order model for reacting flows

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 17f326f3-7ecb-4ed6-a50c-5d9ac8a98609 · outbound

This paper cites Deep Learning combined with singular value decomposition to reconstruct databases in fluid dynamics.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Deep Learning combined with singular value decomposition to reconstruct databases in fluid dynamics

Reference 5

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation d3d87281-2524-4f99-923b-4d0ad062b6a4 · outbound

This paper cites Parente, J.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Parente, J

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 796817c0-45fe-4fc7-8308-73ed1a1fd94c · outbound

This paper cites Scherl, B.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Scherl, B

Reference 7

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 86671bd0-8a7f-4bed-9acf-22b25eb96455 · outbound

This paper cites Le Clainche, J.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Le Clainche, J

Reference 8

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 65dc042e-6464-4669-bd9e-860ef37d5498 · outbound

This paper cites Le Clainche, R.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Le Clainche, R

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 74854c2f-cf7c-4901-b869-41c23fc45178 · outbound

This paper cites Corrochano, G.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Corrochano, G

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 0ce5d232-3946-4451-b883-3bb4c15cf59a · outbound

This paper cites Forecasting through deep learning and modal decomposition in two-phase concentric jets.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Forecasting through deep learning and modal decomposition in two-phase concentric jets

Reference 11

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation b745da89-6ad2-4263-a711-c062a91a3d11 · outbound

This paper cites Huang, T.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Huang, T

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation a7ea72a2-b349-491d-b4f6-ed3a32741eed · outbound

This paper cites Mu˜ noz, H.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Mu˜ noz, H

Reference 13

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation c1b5cef7-e435-4fdd-8f47-f3f11b350038 · outbound

This paper cites Eivazi, S.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Eivazi, S

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-12T12:12:26.349151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation ef4d60a7-e106-44c6-b044-43d7d414fcba · outbound

This paper cites Soto-Valle, S.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Soto-Valle, S

Reference 15

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation dd76562b-a016-41b8-8880-e64fa7ff0dba · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 5f2a6171-3b0f-47d6-bd7c-dc9fbd5db7a3 · outbound

This paper cites Woodward, Y.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Woodward, Y

Reference 17

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 24332378-7db3-4c04-9a46-3f26eb5b85cd · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 18

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 4896d476-e382-4127-8748-b481fb4774fc · outbound

This paper cites Siano, E.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Siano, E

Reference 19

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 996ecd2c-a539-4123-b44a-fec6be0b57e3 · outbound

This paper cites ModelFLOWs-app: data-driven post-processing and reduced order modelling tools.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements ModelFLOWs-app: data-driven post-processing and reduced order modelling tools

Reference 20

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 099b7e3c-40a5-4693-b296-c1ae9d167497 · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 21

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 5cfadbbb-ba60-4313-8aed-3ae57d1f3ed2 · outbound

This paper cites Shallow Neural Networks for Fluid Flow Reconstruction with Limited Sensors.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Shallow Neural Networks for Fluid Flow Reconstruction with Limited Sensors

Reference 22

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local_arxiv, observed 2026-08-12T12:12:25.577939Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 742594b5-4343-48d9-b5ff-4dd4a87c6643 · outbound

This paper cites de Silva, K.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements de Silva, K

Reference 23

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 5f3ad1cb-5094-4a7a-b728-cd827903b73c · outbound

This paper cites Arciniega-Ceballos, M.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Arciniega-Ceballos, M

Reference 24

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation cdb7bcac-496f-4f13-9b6e-e6d2365b417d · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 25

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation c5032b4b-61e4-427b-af66-e5977c329392 · outbound

This paper cites Umargono, J.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Umargono, J

Reference 26

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation d19fc4b0-85fc-4fd4-981d-7beabce3f1da · outbound

This paper cites Sirovich, Turbulence and the dynamic of coherent structures, parts i–iii, Q.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Sirovich, Turbulence and the dynamic of coherent structures, parts i–iii, Q

Reference 27

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 281327ea-d4f8-4321-ad44-acb36b3e5049 · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 28

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 8c80ddec-bda3-40db-956e-8123f1c9365d · outbound

This paper cites Le Clainche, D.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Le Clainche, D

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:12:25.344078Z digest=sha256:d963a2b6c849685a32851ce60bb3a76e5b618b5b05d6439c3298ad4250549226

Observation da6fee25-a231-4690-90d8-ba06923c0bd7 · outbound

This paper cites Parente, J.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Parente, J

Reference 30

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raw_fallback, observed 2026-08-12T12:12:26.179583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.348200Z digest=sha256:8c9f33234e84f849b12de7271c756172a25bf49d1c8e9e5d1dbc424a917ca0e6

Observation 06f4c816-0010-4949-a099-885b0ea4f81c · outbound

This paper cites Rap´ un, F.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Rap´ un, F

Reference 31

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raw_fallback, observed 2026-08-12T12:12:26.165837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.352540Z digest=sha256:0103ecb6ed3afa615f8639a6095350d4fe156833c3756a77a0cd4dd0a50b38c6

Observation 189b78c9-8baa-48f9-bfef-7fc0858b1766 · outbound

This paper cites Manohar, B.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Manohar, B

Reference 32

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raw_fallback, observed 2026-08-12T12:12:26.153080Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation ef1ba9a3-f4cd-46c2-a6bb-3b85ffc9fd8c · outbound

This paper cites Businger, G.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Businger, G

Reference 33

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raw_fallback, observed 2026-08-12T12:12:26.140045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation c909b4a4-1059-41a3-b40b-3d42ac4d5029 · outbound

This paper cites Sommariva, M.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Sommariva, M

Reference 34

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raw_fallback, observed 2026-08-12T12:12:26.126531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation d7c943c7-f64e-4618-a3c6-473171eaddc6 · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 35

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:26.112461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.369595Z digest=sha256:2a8b0273ac5f583c2a1fcf68bf543bc81fc5a13a197bc57d1983f812c3de950f

Observation 0fbc0de5-5707-4d09-8b39-beed6e797a0d · outbound

This paper cites Seshadri, A.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Seshadri, A

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:26.098662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.373546Z digest=sha256:975087c4a97d4992d2d34598489b122bb865ce60cf93f8bfb53c18c19bfd7395

Observation 295bdcfd-f0f2-4acc-bc52-af07f5f22c27 · outbound

This paper cites Kuraria, N.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Kuraria, N

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:26.085377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.377795Z digest=sha256:328ed1d4e865590b897af452e9617665afd5a6a6c4e56ccaeb5cf29f6cb2ed8b

Observation 0373237d-9c46-461c-8abe-e2354019ccb4 · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:26.071884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.381736Z digest=sha256:d797a5fd33a39ff71d3742c6f174fd2f0e717a04d179e71a9a8665e557db8d30

Observation 62dee0b9-c52e-488b-894c-caafa1ab0b7f · outbound

This paper cites Jackson, A finite-element study of the onset of vortex shedding in flow past variously shaped bodies, Journal of fluid Mechanics 182 (1987) 23–45.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Jackson, A finite-element study of the onset of vortex shedding in flow past variously shaped bodies, Journal of fluid Mechanics 182 (1987) 23–45

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:26.058381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.385697Z digest=sha256:22083187e10c9f91805fcb17fcc7cc47e4bb840723182cf8b6038bec456cfb45

Observation c7cea966-a39a-400a-9c9b-a94b0126e93a · outbound

This paper cites Barkley, R.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Barkley, R

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:26.044522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.389712Z digest=sha256:7852ed9e635c805de8be400adb294622d9227e541810e751a2f2864afcdbe3ae

Observation ab6223ca-ba69-43d6-a794-d96c6d96076e · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:26.031070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.394501Z digest=sha256:57e445f922b077665d78590ecafd460f30483b302b11ac95869de4d48b7943e4

Observation 2e9626f5-e131-4189-aecc-e10000c8562b · outbound

This paper cites Towne, S.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Towne, S

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:26.017965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.399336Z digest=sha256:bb9531cd328b3baf333f8fbe39aa17deebd5db082f993503e9a7c97f1e375364

Observation 8f17ee4c-0115-49a5-a9cd-e56671be00d5 · outbound

This paper cites Rodriguez, Development of a test section featuring a flat plate condi- tioned for the study of fully developed turbulent boundary layers using PIV, Ph.D.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Rodriguez, Development of a test section featuring a flat plate condi- tioned for the study of fully developed turbulent boundary layers using PIV, Ph.D

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:26.004698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.403382Z digest=sha256:acee51c47f185796753ae04b816254ec19253189d2fc0736599712b31869a86f

Observation ce457e42-c34b-4b4f-8883-dd05a0574633 · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:25.991085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.407464Z digest=sha256:22b9e9710c57b89864360768f3c308fc94d29569a3df532b1a5e115e5fdde8aa

Observation efaeaf9f-5bfe-418a-95bf-9d0f29f568c1 · outbound

This paper cites Vreman, An eddy-viscosity subgrid-scale model for turbulent shear flow: Algebraic theory and applications, Physics of fluids 16 (2004) 3670–3681.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Vreman, An eddy-viscosity subgrid-scale model for turbulent shear flow: Algebraic theory and applications, Physics of fluids 16 (2004) 3670–3681

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:25.978120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.411561Z digest=sha256:8ddaeda3c0b9987db5190b954b01bd75d3a14bb160bedf80244ba9f39c55ba9e

Observation 73b72ffc-c33b-4298-afae-90f96a67812c · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:25.965079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.415930Z digest=sha256:b76d2c194413f4b0a6e0957f5b688e2262610ad1d21c190b2d8a2828b055bd0c

Observation 8410b088-17f1-446c-a674-819a1c07886a · outbound

This paper cites Mani, Analysis and optimization of numerical sponge layers as a nonreflective boundary treatment, Journal of Computational Physics 231 (2012) 704–716.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Mani, Analysis and optimization of numerical sponge layers as a nonreflective boundary treatment, Journal of Computational Physics 231 (2012) 704–716

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:25.951105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.420428Z digest=sha256:d01a20d0f78deef8408f3ad1dcb346067b8e45ec31aedc6617e5adc2ec13bf27

Observation 72131e39-777b-4e49-82c7-8745d71e403a · outbound

This paper cites Zaman, Asymptotic spreading rate of initially compressible jets—experiment and analysis, Physics of Fluids 10 (1998) 2652–2660.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Zaman, Asymptotic spreading rate of initially compressible jets—experiment and analysis, Physics of Fluids 10 (1998) 2652–2660

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:25.936938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.424469Z digest=sha256:59563ffc424b3e8e08d9e9957294a9e46ec54ccf55d5d2421358712ff855364e

Observation a9114a95-7e59-4f84-9b64-7a897b436158 · outbound

This paper cites Zaman, Spreading characteristics of compressible jets from nozzles of various geometries, Journal of Fluid mechanics 383 (1999) 197–228.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Zaman, Spreading characteristics of compressible jets from nozzles of various geometries, Journal of Fluid mechanics 383 (1999) 197–228

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:25.923586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.428755Z digest=sha256:da9cc9733ca86453c9b9a1bf8cf45e9a5e296d36014a4e530fb592b5cd600c12

Observation 40c1f9c7-e481-4e4d-8d24-5e4d08c2289a · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:25.911232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.432925Z digest=sha256:8fab8aabc5234e6427567bd7a49240ecef7db6597ee0847689b9c1f3a79e9df5

Observation 26dd7783-e8ae-4914-b77d-48eb2ebe339f · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:25.898342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.437227Z digest=sha256:4a001bbe87128ef129d2cd4ab5bf5981d73c6a1ddcab130994c520305a30a41a

Observation abb6b49f-65da-4330-a6d3-77af104fd6d7 · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:25.885586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.441943Z digest=sha256:da4c465ca24878f190552e6c089e2221abaea48a673414968b718c749625c705

Observation 7613c6fb-4aa7-435c-9611-5db7bc49818e · outbound

This paper cites Soft- ware available at https://modelflows.github.io/modelflowsapp/ (2023).

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Soft- ware available at https://modelflows.github.io/modelflowsapp/ (2023)

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:25.872848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.447362Z digest=sha256:c6d89805c53d6d508ec39de7d746af5ebc12a2fd1b51b78a1c3f04e180b18333

Observation d891f6e5-9cca-4382-8ec3-0cebde4e45bb · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 54

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:25.859094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.451424Z digest=sha256:1b90ca7a8397ea653672e36ca66f2b2208970b49bb7b6a7d864a4a8805728b31

Observation 907aa0e6-59ce-4568-8c2f-afc024232616 · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 55

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:25.846056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.455815Z digest=sha256:fb8303b888ea2ad671b11f480ba23a0fb1d1a51b52a751f63b436e93fabdd560

Observation fd1d8e81-26a1-44e2-84d0-36d2a894b3ee · outbound

This paper cites Low-cost singular value decomposition with optimal sensor placement.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Low-cost singular value decomposition with optimal sensor placement

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-12T12:12:25.460150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:12:25.460150Z digest=sha256:97408eae2fbea67c3e5a73ba23313a27eac2d0bdf81fb4ddbfc3900e5d8be54a

Observation c0efc8be-edd4-42a7-8656-3edbfcaeee17 · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:25.832954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.464571Z digest=sha256:38aab9641de5d082249a2abe6f849d3185467140c682c51c7497b5fafeb67160

Observation 560860a0-2657-426c-a4d1-3b6ffd0ebb73 · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 58

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:25.819731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.468517Z digest=sha256:56ede545e1892319c35f4f9461f2fa318a5c8a130205a1073e859b15e5b70162

Observation afbb78b0-6d5e-473e-9dc7-60500af5d3b1 · outbound

This paper cites Iuliano, D.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Iuliano, D

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:25.806700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.472938Z digest=sha256:c1c19602d11b5a56a600c7a189683e6dffec163bf43103bae376d86004062947

Observation 4ffdc02a-13d3-4878-81d3-69e28b9e01c5 · outbound

This paper cites Freitag, B.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Freitag, B

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:25.792373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.476998Z digest=sha256:8705a559ca5ab71dcd4efe09f96392ecad58ae4295b8c1d066cc0280a648e64f

Observation ad1c028d-ef24-47ec-b1b9-6af28ad8f3e0 · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 61

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:25.778370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.481300Z digest=sha256:c656d835ca7dc5bafa9e1e1795dc8e21ebfef55ea20aa2fd2b5dc68e2f340e97

Observation 9a0f1f51-84b9-4715-9438-f806e4448afa · outbound

This paper cites Guemes, S.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Guemes, S

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:25.764316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.485250Z digest=sha256:cbdce7a9fc0165830ae9ae80280c30e4fca47c29bfbae00ba3153b7965f9853f

Observation 51da6212-907c-4d80-b5f4-45b5752455bb · outbound

This paper cites Discetti, M.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Discetti, M

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:25.750548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.489285Z digest=sha256:86279835aa6471d8d2ac54db5474762f6939331ffb3dfcdef7ac9861bef28ad4

Observation d669710b-2fdd-4360-b74b-79040f9cacec · outbound

This paper cites Guastoni, A.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Guastoni, A

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:25.737009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.493394Z digest=sha256:41a761d99ba2508f3f9d4fbbd7b13872ca5e0f5e97929acdde2014d8ae4a67c4

Observation d79ebf72-0308-44f5-829a-8fe0e1efbc71 · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 65

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:25.723149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.497357Z digest=sha256:cfa04f9201f49347d2b44ebbef1895eae8fc8e5af1cee3fba3a433df731a2875

Observation 4abc7a97-9bef-4705-a1ca-6b52dd102a08 · outbound

This paper cites De Lathawer, B.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements De Lathawer, B

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:25.709812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.501429Z digest=sha256:73540796258da3defb37b1b1b4c9ef8a18da7c18b4641381a28756f3e7b23e6e

Observation 93cfd0f8-0c6a-4149-b98e-25436b401bf3 · outbound

This paper cites De Lathawer, B.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements De Lathawer, B

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:12:25.696531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.505318Z digest=sha256:8839e71d977ca73dacc502482fc88b48167f06243b49d0621ee9010d4bf46a10

Observation 50f409c3-6852-4811-aac0-16d29725440c · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 68

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:25.683101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.509400Z digest=sha256:7a90b022d251224874501bc6f14587484810f72c6f31aad30a7f7921c780ff86

Observation 580c4779-475f-453e-90b8-1636482a50b2 · outbound

This paper cites an unresolved cited work.

LC-SVD-DLinear: A low-cost physics-based hybrid machine learning model for data forecasting using sparse measurements Unresolved cited work

Reference 69

Resolution
unresolved
raw_fallback, observed 2026-08-12T12:12:25.668485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T12:12:25.513677Z digest=sha256:799f82c6702088bd10c4f13d77365e4fb7bcfe372ead7f1ee2ca04f741873642

Pith citing papers

No inbound Pith citation observations are available.