Paper Citation Record · LEDGER

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling

As of 9 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 2 inbound Pith citation observations for arXiv:2506.09721.

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

pith.paper-citation-record.v1
2506.09721 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:49:08.635748Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T10:36:46.152944Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

53 of 53 outbound references displayed

verified exact0
verified fuzzy45
unresolved6
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3e55d7a5-29b6-49cb-9a98-5ab29d625dcf · outbound

This paper cites VIII International Conference on Computational Methods in Marine Engineering (2019).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling VIII International Conference on Computational Methods in Marine Engineering (2019)

Reference 1

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Observation 1e085538-1188-4e46-96c3-3b581f4d940b · outbound

This paper cites Journal of Scientific Computing, 94, 1-30 (2023).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Journal of Scientific Computing, 94, 1-30 (2023)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:18.363922Z

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Observation 60c2c7f3-733c-48c6-8007-4ecaeec86661 · outbound

This paper cites an unresolved cited work.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Unresolved cited work

Reference 3

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Observation e23d2569-7b96-42d1-a5d2-6532a5813d5a · outbound

This paper cites Numerical Methods in Engineering, 125, e7426 (2024).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Numerical Methods in Engineering, 125, e7426 (2024)

Reference 4

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Observation 7943edd5-34f4-4cb1-aa4f-ffb98a8859f0 · outbound

This paper cites Numerical Methods in Engineering, 124, 1193-1210 (2022).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Numerical Methods in Engineering, 124, 1193-1210 (2022)

Reference 5

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Observation dc4d37ab-3bfd-40ca-a692-8c6839278810 · outbound

This paper cites Computers & Mathematics with Applications, 151, 115-127 (2023).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Computers & Mathematics with Applications, 151, 115-127 (2023)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:17.219295Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b85f4e12-6eb1-47b2-b142-ae94b01e8e30 · outbound

This paper cites Enhancing non-intrusive Reduced Order Models with space-dependent aggregation methods.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Enhancing non-intrusive Reduced Order Models with space-dependent aggregation methods

Reference 7

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Observation 414a96d7-2cc2-48c1-81b7-ce1507a37108 · outbound

This paper cites Optimal Transport-inspired Deep Learning Framework for Slow-Decaying Kolmogorov n-width Problems: Exploiting Sinkhorn Loss and Wasserstein Kernel.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Optimal Transport-inspired Deep Learning Framework for Slow-Decaying Kolmogorov n-width Problems: Exploiting Sinkhorn Loss and Wasserstein Kernel

Reference 8

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Observation 24c9e66d-da66-456d-9786-95782cc9873b · outbound

This paper cites Computer Methods in Applied Mechanics and Engineering,392, 114687 (2022).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Computer Methods in Applied Mechanics and Engineering,392, 114687 (2022)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:16.930292Z

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Observation eb88e3e9-9c45-4c37-96f9-fbbe872e0c0f · outbound

This paper cites Computers & Fluids, 254, 105813 (2023).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Computers & Fluids, 254, 105813 (2023)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:16.699242Z

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Observation f97a1ebd-919f-4de3-83cb-2008d342f08b · outbound

This paper cites The Journal of Open Source Software, 3, 661 (2018).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling The Journal of Open Source Software, 3, 661 (2018)

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:16.449388Z

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Observation cbfe8114-820d-4c0d-9a90-b7e70b4897f0 · outbound

This paper cites International Journal for Numerical Methods in Fluids, 83, 291–306 (2016).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling International Journal for Numerical Methods in Fluids, 83, 291–306 (2016)

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:16.393907Z

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Observation 1a916c22-9aa4-492d-be7f-9ced3042bcef · outbound

This paper cites & Schwab, C.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling & Schwab, C

Reference 13

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Observation 9520529a-9757-4e38-94d4-27e55d53e035 · outbound

This paper cites & Allen, M.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling & Allen, M

Reference 14

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Observation 3c453910-d4f8-4f4a-a193-9f025cb12554 · outbound

This paper cites an unresolved cited work.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Unresolved cited work

Reference 15

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Observation e731b788-7e9b-46c7-a379-2ab42cada18e · outbound

This paper cites Acta Astronautica, 185, 25–36 (2021).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Acta Astronautica, 185, 25–36 (2021)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:15.956613Z

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Observation 0ccf4e14-0d40-4088-931d-e578dca84a3e · outbound

This paper cites Journal of Computational Physics, 439, 110378 (2021).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Journal of Computational Physics, 439, 110378 (2021)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:15.859266Z

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Observation c35243f9-72a7-400a-823b-b73313d8d056 · outbound

This paper cites Journal of Computational and Applied Mathematics, 390, 113372 (2021).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Journal of Computational and Applied Mathematics, 390, 113372 (2021)

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:15.751180Z

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Observation 861b0932-0255-4a48-a8f2-daa9b120b7ab · outbound

This paper cites On: D’Elia, M., Gunzburger, M., Rozza, G.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling On: D’Elia, M., Gunzburger, M., Rozza, G

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:15.638608Z

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Observation e157a033-f2bc-4d67-9669-42f3cf0f9dcb · outbound

This paper cites Computers & Mathematics with Applications, 143, 383-396 (2023).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Computers & Mathematics with Applications, 143, 383-396 (2023)

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:15.505827Z

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Observation 9482be0c-4619-4fae-a1ac-8fac107370c8 · outbound

This paper cites The Journal of Open Source Software, 8, 5352 (2023).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling The Journal of Open Source Software, 8, 5352 (2023)

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:15.410342Z

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Observation 072c2bdd-5fa1-4d8f-be11-e17fbd15613a · outbound

This paper cites Scientific Reports, 14, 3826 (2024).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Scientific Reports, 14, 3826 (2024)

Reference 22

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Observation 9beb0c08-d1f1-481f-9ad5-be44273bde65 · outbound

This paper cites SIAM, Philadelphia (2020).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling SIAM, Philadelphia (2020)

Reference 23

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Observation 4aebff26-8477-42e9-889a-fd87d8efff11 · outbound

This paper cites Computer Methods in Applied Mechanics and Engineering, 423, 116823 (2024).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Computer Methods in Applied Mechanics and Engineering, 423, 116823 (2024)

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:14.814494Z

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Observation 3b951024-262b-459b-b5c9-a8a9fa42bbb8 · outbound

This paper cites European Conference on Computer Vision (2018).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling European Conference on Computer Vision (2018)

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:14.680074Z

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Observation 15ee575d-a724-4e8d-b243-58de191eec43 · outbound

This paper cites 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (2020).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (2020)

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:14.508703Z

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Observation e137547d-0fc5-4f2d-a578-95a1317ed93d · outbound

This paper cites MIT Press, Cambridge (2016).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling MIT Press, Cambridge (2016)

Reference 27

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Observation bbe3a5b7-9b57-4373-b712-f28da230a251 · outbound

This paper cites Noncompact uniform universal approximation.Neural Networks.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Noncompact uniform universal approximation.Neural Networks

Reference 28

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Observation e44b621f-dcb4-4cbb-a20a-1db60a150290 · outbound

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Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Unresolved cited work

Reference 29

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Observation 58aeead9-2a63-4f54-8c47-d91889e503a4 · outbound

This paper cites International Conference on Learning Representations (2014).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling International Conference on Learning Representations (2014)

Reference 30

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Observation 040175e0-ce22-4236-a89c-129f7064a4f7 · outbound

This paper cites Advances in Neural Information Processing Systems 33 (2020).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Advances in Neural Information Processing Systems 33 (2020)

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:13.452222Z

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Observation 88c05383-c0b3-4a68-b5db-6ee114ae47bd · outbound

This paper cites and Courville, A.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling and Courville, A

Reference 32

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Observation ff351568-1a77-4f04-ab73-6903fde2d74e · outbound

This paper cites International Conference on Learning Representations (2016).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling International Conference on Learning Representations (2016)

Reference 33

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Observation 347a16c1-9c3d-42c4-b436-06436c63306f · outbound

This paper cites Pro- ceedings of the 34th International Conference on Machine Learning (2017).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Pro- ceedings of the 34th International Conference on Machine Learning (2017)

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:12.625976Z

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Observation 8d75f503-aab2-47be-889f-221cb72f60cc · outbound

This paper cites Sason and S.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Sason and S

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:12.353418Z

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Observation 4417c9b6-ecdd-404a-9a8b-70dbd641051f · outbound

This paper cites On Choosing and Bounding Probability Metrics.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling On Choosing and Bounding Probability Metrics

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:12.064718Z

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Observation 9e40d7af-92f4-4e57-9417-6cf5fc01a72c · outbound

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Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Unresolved cited work

Reference 37

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Observation 318a4de4-a997-4183-bfa5-d047e4960772 · outbound

This paper cites an unresolved cited work.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Unresolved cited work

Reference 38

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Observation e82d7e92-6515-4060-b5fa-ae2d857ff6de · outbound

This paper cites & Cresswell, J.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling & Cresswell, J

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:11.324005Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1b3ee558-8dd5-46ac-8d92-8198128046f0 · outbound

This paper cites BEGAN: Boundary Equilibrium Generative Adversarial Networks.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling BEGAN: Boundary Equilibrium Generative Adversarial Networks

Reference 40

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Source-reported events for the cited work

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Observation d3b47733-2284-4d5a-aa68-25c41c5571de · outbound

This paper cites Proceedings of the 32nd International Conference on Machine Learning (2015).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Proceedings of the 32nd International Conference on Machine Learning (2015)

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:11.133693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 56db5242-7868-4a3a-a15e-3c731f5548fb · outbound

This paper cites Ad- vances in Neural Information Processing Systems 32 (2019).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Ad- vances in Neural Information Processing Systems 32 (2019)

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:11.011816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a8adac97-719a-4f1c-b846-98873b178f0e · outbound

This paper cites Software Impacts, 7 (2021).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Software Impacts, 7 (2021)

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:10.841736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0c875a71-7cb0-4112-b162-6f84c29fb90e · outbound

This paper cites MIT Press, Cambridge (2006) Generative Models for Parameter Space Reduction applied to Reduced Order Modelling 25.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling MIT Press, Cambridge (2006) Generative Models for Parameter Space Reduction applied to Reduced Order Modelling 25

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:10.632999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c4caa08c-dbde-4778-83ed-36399ab84905 · outbound

This paper cites Cambridge University Press, Cambridge (2009).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Cambridge University Press, Cambridge (2009)

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:10.456259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 97e3e90d-096b-4bb1-8e2b-2a37af0981f6 · outbound

This paper cites 24, 303(2005).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling 24, 303(2005)

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:10.287002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation daf65665-5fcc-4749-8f92-e690c02f693e · outbound

This paper cites & Duchesnay, E.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling & Duchesnay, E

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:10.125835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 496bab7f-8d3c-43a0-92ee-31784d665874 · outbound

This paper cites Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques - SIGGRAPH ’94, ACM Press (1994).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques - SIGGRAPH ’94, ACM Press (1994)

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:09.943717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c21b2d63-d0e5-4c2d-be53-1d5c156b9f30 · outbound

This paper cites SNAME Maritime Convention, SNAME (2019).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling SNAME Maritime Convention, SNAME (2019)

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:09.731363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a2677fb8-e395-4661-9ddd-69961dabb93b · outbound

This paper cites Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2017).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (2017)

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:09.562708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 640f4c19-4e5c-45c1-989a-5a3c25187353 · outbound

This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision (2019).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Proceedings of the IEEE/CVF International Conference on Computer Vision (2019)

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:09.445866Z

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Observation f4200276-03ae-4f6d-8e36-c434925b657d · outbound

This paper cites Advanced Modeling and Simulation in Engineering Sciences, 9, 8 (2022).

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Advanced Modeling and Simulation in Engineering Sciences, 9, 8 (2022)

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:49:09.271038Z

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This paper cites Communications in Applied and Industrial Mathematics (2013) 4 Appendix Here we describe the details of the architectures and hyperparameters adopted to train the Generative Models.

Generative Models for Parameter Space Reduction applied to Reduced Order Modelling Communications in Applied and Industrial Mathematics (2013) 4 Appendix Here we describe the details of the architectures and hyperparameters adopted to train the Generative Models

Reference 53

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Pith citing papers

Observation 27b8af03-ee49-4880-95c1-d0361cae1e1f · inbound

A Structured Review of Reduced Order Modeling for Domain Decomposition Problems: State of the Art and Perspectives cites this paper.

A Structured Review of Reduced Order Modeling for Domain Decomposition Problems: State of the Art and Perspectives Generative Models for Parameter Space Reduction applied to Reduced Order Modelling

Reference 204

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A Generative Model-Free Form Deformation Approach for the Generation of Mesh Motions with Applications to PDE cites this paper.

A Generative Model-Free Form Deformation Approach for the Generation of Mesh Motions with Applications to PDE Generative Models for Parameter Space Reduction applied to Reduced Order Modelling

Reference 6

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