Paper Citation Record · LEDGER

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences

As of 7 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2608.04708.

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

pith.paper-citation-record.v1
2608.04708 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:32:38.557667Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

51 of 51 outbound references displayed

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verified fuzzy4
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Outbound references

Observation a234cfcb-4940-4266-a6e0-8272845c62c2 · outbound

This paper cites Huthwaite, Accelerated finite element elastodynamic simulations using the gpu, Journal of Computational Physics 257 (2014) 687–707.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Huthwaite, Accelerated finite element elastodynamic simulations using the gpu, Journal of Computational Physics 257 (2014) 687–707

Reference 1

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Observation 46cfe69f-257c-4d4d-b836-044027da4036 · outbound

This paper cites Bernardini, D.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Bernardini, D

Reference 2

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Observation 32034a4e-c942-4797-845e-72ba43525e5e · outbound

This paper cites Drucker, C.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Drucker, C

Reference 3

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Observation dddce4b9-f861-4985-a299-1b174e0ed3f2 · outbound

This paper cites an unresolved cited work.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 4

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Observation 93f2f7a8-8e09-41f7-a3ff-273e06205f3a · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 5

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Observation 8e311e95-82b8-4824-86ab-70922b7da170 · outbound

This paper cites an unresolved cited work.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 6

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Observation 8943fc4d-715a-4c8f-bc65-b281e9f5e998 · outbound

This paper cites Chatterjee, An introduction to the proper orthogonal decomposition, Current Science 78 (7) (2000) 808–817.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Chatterjee, An introduction to the proper orthogonal decomposition, Current Science 78 (7) (2000) 808–817

Reference 7

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Observation afb7bf7f-ef13-4b43-9dc1-6fd0200a6a7b · outbound

This paper cites Pakravan, P.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Pakravan, P

Reference 8

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Observation 7b42f8e2-7fae-420d-9864-3d7f09af0b9a · outbound

This paper cites Neural Inverse Operators for Solving PDE Inverse Problems.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Neural Inverse Operators for Solving PDE Inverse Problems

Reference 9

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Observation 4cd29b71-efc0-4352-a42f-47dfbf396425 · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 10

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Observation f708e224-8526-4736-b7a6-a99635e3c0d1 · outbound

This paper cites Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems

Reference 11

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Observation 35730d36-36a1-4e4d-8d38-21a0957a0270 · outbound

This paper cites an unresolved cited work.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 12

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Observation 6b5999c6-2697-4c28-ba5a-a2ee075de49b · outbound

This paper cites an unresolved cited work.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 13

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Observation 57db7549-2b5d-4cfb-97ec-c0a1d46a8ac9 · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 14

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Observation a7d4f669-b43e-42de-817f-adc4d32a68d4 · outbound

This paper cites Murtagh, Multilayer perceptrons for classification and regression, Neurocomputing 2 (5–6) (1991) 183–197.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Murtagh, Multilayer perceptrons for classification and regression, Neurocomputing 2 (5–6) (1991) 183–197

Reference 15

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Observation 427ab01e-6ed6-43f7-b123-2259c07327e1 · outbound

This paper cites Popescu, V.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Popescu, V

Reference 16

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Observation 626d55a1-950b-42ac-b031-8b77b73b7a3e · outbound

This paper cites Lecun, L.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Lecun, L

Reference 17

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Observation 2db6ba29-25e9-48a7-8eb7-93390d454530 · outbound

This paper cites Raissi, P.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Raissi, P

Reference 18

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Observation 96b601df-adac-4a94-b06e-279ad86c1ae8 · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 19

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Observation 1f007116-23d8-4c08-a1a2-75621fd337ac · outbound

This paper cites Neural Operator: Learning Maps Between Function Spaces.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Neural Operator: Learning Maps Between Function Spaces

Reference 20

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Observation 70c50a24-9292-4f72-a438-15da9a0296b7 · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 21

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Observation 0cf2f59b-630c-4cb9-be40-e71dd6f0c008 · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 22

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Observation 693ad308-5b47-4098-91e2-d0099d52b146 · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 23

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Source-reported events for the cited work

correction dated 2016-05-25. Source: crossref record 10.1016/j.cma.2016.05.004->10.1016/j.cma.2016.03.022:correction, observed 2026-07-11T03:18:23.212888+00:00. This notice travels one citation hop only.

Observation 541370c1-8b3c-4e85-aa00-33b22689ce13 · outbound

This paper cites Koziel, A.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Koziel, A

Reference 24

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Observation e24da394-bb3d-4529-8c59-f16e13803c29 · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 25

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Observation b5d14690-a9be-4ac4-a06f-2538595fc661 · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 26

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Observation e430470f-7441-4f82-a2d5-f6d09d09b77d · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 27

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Observation 07761ee6-50d3-4660-9d39-3e6f92032d71 · outbound

This paper cites Chakraborty, Transfer learning based multi-fidelity physics informed deep neural network, Journal of Computational Physics 426 (2021) 109942.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Chakraborty, Transfer learning based multi-fidelity physics informed deep neural network, Journal of Computational Physics 426 (2021) 109942

Reference 28

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Observation 348b0c69-1dfe-4d00-b852-5ece22db0c83 · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 29

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Observation b658b964-b7fb-40dc-9a42-bd9e414957d5 · outbound

This paper cites Multi-fidelity Fourier Neural Operator for Fast Modeling of Large-Scale Geological Carbon Storage.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Multi-fidelity Fourier Neural Operator for Fast Modeling of Large-Scale Geological Carbon Storage

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-06T18:32:41.817536Z

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Observation 79f9cbe4-8234-4a01-b9ab-d7c610daba01 · outbound

This paper cites Tripura, A.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Tripura, A

Reference 31

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Observation 4f3dfb7c-a9ab-4ce5-a450-ba3cef6c7d22 · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 32

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This paper cites Renard, S.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Renard, S

Reference 33

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Observation feb4b950-51f4-47bb-8372-8ee82ad34bd7 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Gaussian Error Linear Units (GELUs)

Reference 34

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Observation 4c7e9202-a83e-497a-b2e1-8bb757f4b02b · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning

Reference 35

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Observation 20334d54-9933-4413-86f1-e1b3b6bb3eb7 · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Deep Learning using Rectified Linear Units (ReLU)

Reference 36

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Observation 5f339f16-7127-4b8f-9cad-aace021614a2 · outbound

This paper cites Neural Operator: Graph Kernel Network for Partial Differential Equations.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Neural Operator: Graph Kernel Network for Partial Differential Equations

Reference 37

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Observation 350d6a15-f45f-422f-8a81-f25cd3ca3773 · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Fourier Neural Operator for Parametric Partial Differential Equations

Reference 38

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Observation a49c5159-3a1f-43ca-bf33-bae83a179f7d · outbound

This paper cites Eldred, A.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Eldred, A

Reference 39

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Observation 0322b4c2-7138-45a7-b85f-1e1701272185 · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 40

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This paper cites Leifsson, S.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Leifsson, S

Reference 41

Resolution: verified exact; doi, observed 2026-08-06T18:32:40.067635Z

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Observation d4edb0b5-9db6-4faf-971b-88325e8545a8 · outbound

This paper cites Zhang, N.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Zhang, N

Reference 42

Resolution: verified exact; doi, observed 2026-08-06T18:32:39.724787Z

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Observation 611e2b71-11b3-4cc5-8357-e515cd07a7ae · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 43

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Observation 40088963-c696-47e4-96de-6602d801335c · outbound

This paper cites Giselle Fern ´andez-Godino, Review of multi-fidelity models, Advances in Computational Science and Engineering 1 (4) (2023) 351–400.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Giselle Fern ´andez-Godino, Review of multi-fidelity models, Advances in Computational Science and Engineering 1 (4) (2023) 351–400

Reference 44

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Observation 8c11a7df-a94a-4878-93bc-ca682e5a1e7f · outbound

This paper cites Babaee, P.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Babaee, P

Reference 45

Resolution: verified exact; doi, observed 2026-08-06T18:32:39.094940Z

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Observation 4319c04c-da9b-4fd7-bf6d-74be3168b58a · outbound

This paper cites Perdikaris, M.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Perdikaris, M

Reference 46

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Observation f9d7f3a3-d5c9-4ea9-9ad0-46c7de010c7a · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 47

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Observation 62587f2e-1c49-44b1-90d5-ec4d7b3d875b · outbound

This paper cites Zakaria, A.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Zakaria, A

Reference 48

Resolution: verified exact; doi, observed 2026-08-06T18:32:38.828499Z

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Observation d70bbc02-8e3a-4486-9e5b-3608c21bc306 · outbound

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Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-08-06T18:32:44.246335Z

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Observation 027f305a-ebc0-4b84-ad61-bc8d65b90486 · outbound

This paper cites Lippe, B.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Lippe, B

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T18:32:44.053686Z

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Observation 5f0b2c30-c2f1-4bef-a2ea-04b9eb8a2795 · outbound

This paper cites Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation.

Benchmarking Multi-fidelity Neural Operators on Complex PDE Problems with Non-trivial Fidelity Differences Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation

Reference 51

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Pith citing papers

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