Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence | Paper Citation Record

Observation eb9e190b-5441-4e8b-a536-f6f2c7f2774b · outbound

This paper cites These approaches offer the advantage of not requiring a dedicated RANS solver, as the RANS model can be incorporated directly into the loss function [35, 36].

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence These approaches offer the advantage of not requiring a dedicated RANS solver, as the RANS model can be incorporated directly into the loss function [35, 36]

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.714735Z

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Observation 002f14c3-b657-4433-bc8d-0a06eed78902 · outbound

This paper cites This makes it possible to set the value ofCε2 to 1.92, as is commonly done in most RANS models [49].

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence This makes it possible to set the value ofCε2 to 1.92, as is commonly done in most RANS models [49]

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.743360Z

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This paper cites As can be seen, the calibrated coefficients obtained from the different approaches—regression, Bayesian calibration, and PINN-C 0D or 1D— are in good agreement.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence As can be seen, the calibrated coefficients obtained from the different approaches—regression, Bayesian calibration, and PINN-C 0D or 1D— are in good agreement

Reference 3

Resolution: malformed identifier; raw_fallback, observed 2026-07-09T21:46:34.734467Z

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Observation d6f2265e-4ece-4dd7-99df-95fea595f54c · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.757075Z

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Observation 156e24f0-2505-40fd-b8c8-6765d47edacb · outbound

This paper cites The idea for the calibration is similar to the one performed by Nadiga et al.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence The idea for the calibration is similar to the one performed by Nadiga et al

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.672421Z

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Observation 05c83846-0641-435d-8939-8c63ff665a8c · outbound

This paper cites 27 0.13435 0.13440 0.13445 σc 0 10000 20000p.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence 27 0.13435 0.13440 0.13445 σc 0 10000 20000p

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.723900Z

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Observation f7fabe14-10f9-4e60-8c44-0114afce3901 · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.744954Z

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Observation 4461f675-43f2-420a-b5be-cfa485ac3f09 · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.773852Z

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Observation 8b95ee41-dccf-4660-8b87-c832d997945d · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.682194Z

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Observation 38a8545f-6d06-4e70-9138-a082567fbf95 · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.720455Z

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Observation 24578c8c-aa5e-4e33-b0d7-58641c163da3 · outbound

This paper cites Zhou, Physics Reports720-722, 1 (2017), ISSN 0370-1573, rayleigh–Taylor and Richt- myer–Meshkov instability induced flow, turbulence, and mixing.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Zhou, Physics Reports720-722, 1 (2017), ISSN 0370-1573, rayleigh–Taylor and Richt- myer–Meshkov instability induced flow, turbulence, and mixing

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.692706Z

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Observation 89cd674e-ec9f-4a8a-9a25-5dc7ac49e2cf · outbound

This paper cites Zhou, Physics Reports723-725, 1 (2017), ISSN 0370-1573, rayleigh–Taylor and Richt- myer–Meshkov instability induced flow, turbulence, and mixing.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Zhou, Physics Reports723-725, 1 (2017), ISSN 0370-1573, rayleigh–Taylor and Richt- myer–Meshkov instability induced flow, turbulence, and mixing

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.722416Z

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Observation eed14003-9697-4d85-87fc-ce2393a2df50 · outbound

This paper cites Lindl, Physics of Plasmas2, 3933 (1995), ISSN 1070-664X, 1089- 7674, URLhttps://pubs.aip.org/pop/article/2/11/3933/261855/ Development-of-the-indirect-drive-approach-to.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Lindl, Physics of Plasmas2, 3933 (1995), ISSN 1070-664X, 1089- 7674, URLhttps://pubs.aip.org/pop/article/2/11/3933/261855/ Development-of-the-indirect-drive-approach-to

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.710093Z

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Observation d80f30eb-d3e5-4885-ba1e-dec3c19358ae · outbound

This paper cites Betti and O.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Betti and O

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.718412Z

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Observation 8085d1c7-bd91-466b-aaa3-554ce28611a9 · outbound

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Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 15

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correction dated 2023-01-25. Source: crossref record 10.1073/pnas.2221966120->10.1073/pnas.1717236115:correction, observed 2026-07-11T02:56:45.779481+00:00. This notice travels one citation hop only.

Observation 4debe538-9432-4234-bf42-19057d07da79 · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.766750Z

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Observation 736e3ea0-e20e-491b-b9be-3ddde87067f8 · outbound

This paper cites Computation at the edge of chaos: Phase transitions and emergent computation.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Computation at the edge of chaos: Phase transitions and emergent computation

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-09T21:46:34.587164Z

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Observation 013e3b55-d9a8-4615-834a-56442b78deae · outbound

This paper cites Chandrasekhar,Hydrodynamic and hydromagnetic stability(Courier Corporation, 2013).

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Chandrasekhar,Hydrodynamic and hydromagnetic stability(Courier Corporation, 2013)

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.660371Z

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Observation 68b5e2d1-8567-4cea-85f9-b01e979ae3d5 · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 19

Resolution: verified exact; doi, observed 2026-07-09T21:46:34.548902Z

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Observation 9a0cd5c6-f2a2-4087-8294-9eda56437d07 · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.770098Z

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Observation 244628aa-0a3e-4fab-8100-9f47fb891523 · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.730926Z

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Observation f6103ffc-0c4d-4fe3-a6cf-433d6beb9c6e · outbound

This paper cites Thévenin, B.-J.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Thévenin, B.-J

Reference 22

Resolution: verified exact; doi, observed 2026-07-09T21:46:34.560098Z

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Observation 2486242b-8591-44fc-b694-3ba8c41e611e · outbound

This paper cites Thévenin and B.-J.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Thévenin and B.-J

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.688427Z

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Observation 8036a08a-242a-4a39-8b36-3bc7290d80de · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 24

Resolution: verified exact; doi, observed 2026-07-09T21:46:34.558513Z

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Observation 37e37b86-486e-48a4-b813-099a8b9318fe · outbound

This paper cites Dimonte, Physics of Plasmas7, 2255 (2000), ISSN 1070-664X, 1089-7674, URLhttps://pubs.aip.org/pop/article/7/6/2255/103605/ Spanwise-homogeneous-buoyancy-drag-model-for.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Dimonte, Physics of Plasmas7, 2255 (2000), ISSN 1070-664X, 1089-7674, URLhttps://pubs.aip.org/pop/article/7/6/2255/103605/ Spanwise-homogeneous-buoyancy-drag-model-for

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.722150Z

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Observation 4388afa4-e532-4c37-b72f-241f9d915471 · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 26

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.731640Z

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Observation f18cc7b8-fd60-40fd-8176-9c021560d621 · outbound

This paper cites Schilling, Physica D: Nonlinear Phenomena402, 132238 (2020).

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Schilling, Physica D: Nonlinear Phenomena402, 132238 (2020)

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.701450Z

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Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 28

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Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.751850Z

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Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.733641Z

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Observation 6b812ae4-d33b-439e-926a-6fa128279ff4 · outbound

This paper cites Rollin and M.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Rollin and M

Reference 31

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Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.737925Z

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Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 33

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.739722Z

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Observation c56a6b8a-84f2-4226-9348-92ced6500161 · outbound

This paper cites Duraisamy, G.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Duraisamy, G

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.712647Z

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Observation 38e65601-a317-45a7-a91d-efaa91bf3a92 · outbound

This paper cites Duraisamy, Phys.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Duraisamy, Phys

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.768406Z

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Observation 209a1919-d70b-4f6b-b660-11d3c29b8317 · outbound

This paper cites Xiao and P.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Xiao and P

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.735612Z

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Observation 18db1c38-cc68-46c8-b11f-2104aa0a3d02 · outbound

This paper cites Boureima, V.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Boureima, V

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.705844Z

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Observation 6fa18a88-1352-4916-8df9-a0d71e4ea557 · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.753531Z

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Observation 9f55914d-1b1a-4e8e-ba2f-41b215e0e3ba · outbound

This paper cites Edeling, P.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Edeling, P

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.740711Z

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Observation bd325886-7026-4633-8cf1-c311b6426261 · outbound

This paper cites Nadiga, C.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Nadiga, C

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.748619Z

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Observation ee3fae19-9c7c-4555-80cc-e70da44a1795 · outbound

This paper cites Raissi, P.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Raissi, P

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.696296Z

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Observation 02c01de8-a715-4b5f-a5ef-d78df99b8f09 · outbound

This paper cites Eivazi, M.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Eivazi, M

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.690234Z

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Observation b01b0147-34c6-45b0-85c6-741f4ae07730 · outbound

This paper cites Xiao, T.-C.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Xiao, T.-C

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.708286Z

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Observation d34a888d-8698-4924-9cb5-f26d4d7e98e0 · outbound

This paper cites Zhang, K.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Zhang, K

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.750239Z

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Observation cf1d0975-acf4-465f-a6e2-7629fedf37a5 · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.771946Z

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Observation 1cf51b65-3ca8-45a3-9016-a808bbd643b2 · outbound

This paper cites Patel, V.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Patel, V

Reference 46

Resolution: verified exact; doi, observed 2026-07-09T21:46:34.546781Z

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Observation 59198cb2-c813-42d2-ad08-653bca54d239 · outbound

This paper cites Kenjereš and K.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Kenjereš and K

Reference 47

Resolution: verified exact; doi, observed 2026-07-09T21:46:34.550699Z

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Observation 1eb38a9a-14f1-4bd7-b1ca-898affda4c3f · outbound

This paper cites Schilling and N.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Schilling and N

Reference 48

Resolution: verified exact; doi, observed 2026-07-09T21:46:34.556573Z

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Observation 17179173-1d15-4dbd-9f81-169c4501a233 · outbound

This paper cites Thévenin, B.-J.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Thévenin, B.-J

Reference 49

Resolution: verified exact; doi, observed 2026-07-09T21:46:34.562163Z

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Observation 4d9ae97b-6a3c-4ee2-9d8d-069bb15622f7 · outbound

This paper cites Gréa and A.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Gréa and A

Reference 50

Resolution: verified exact; doi, observed 2026-07-09T21:46:34.532204Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b14da91e-5a1b-40c1-b31f-efd7ece5946e · outbound

This paper cites Briard, L.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Briard, L

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.677242Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 00b3294a-1c0c-4ee8-9443-8c0b63c09c05 · outbound

This paper cites Briard, B.-J.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Briard, B.-J

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.760581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8d9ee2e7-f7ea-42d7-bcb7-17279a827b50 · outbound

This paper cites Briard, B.-J.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Briard, B.-J

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.741408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c01c982f-2eb6-45f8-bd03-1758be76cd34 · outbound

This paper cites A comparative study of the turbulent Rayleigh-Taylor instability using high-resolution three-dimensional numerical simulations: The Alpha-Group collaboration.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence A comparative study of the turbulent Rayleigh-Taylor instability using high-resolution three-dimensional numerical simulations: The Alpha-Group collaboration

Reference 54

Resolution: verified exact; doi, observed 2026-07-09T21:46:34.536395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 002f4eab-2af9-4ca1-8cc5-ba02233e74b3 · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 55

Resolution: verified exact; doi, observed 2026-07-09T21:46:34.554666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9666a9a5-43dd-4ebd-af1f-df0d17ccccab · outbound

This paper cites Hanjalić, Annual Review of Fluid Mechanics34, 321–347 (2002), ISSN 1545- 4479, URLhttps://www.annualreviews.org/content/journals/10.1146/annurev.fluid.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Hanjalić, Annual Review of Fluid Mechanics34, 321–347 (2002), ISSN 1545- 4479, URLhttps://www.annualreviews.org/content/journals/10.1146/annurev.fluid

Reference 56

Resolution: malformed identifier; doi_truncated, observed 2026-07-09T21:46:34.541633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 565cea37-482b-4341-86f7-19ca22c23c91 · outbound

This paper cites Meldi and P.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Meldi and P

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.663095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation af8f9ceb-30e6-42d6-b366-309cd0604e77 · outbound

This paper cites Schiestel,Modeling and simulation of turbulent flows, vol.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Schiestel,Modeling and simulation of turbulent flows, vol

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.736339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2ee092f0-6449-4e4b-8768-693daf4ddf62 · outbound

This paper cites Gréa, Journal of Turbulence16, 184 (2015).

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Gréa, Journal of Turbulence16, 184 (2015)

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.728413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d170ad82-54e4-414f-9060-1fd7372370c3 · outbound

This paper cites Griffond, O.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Griffond, O

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.746829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f24fb898-e228-4ba8-9687-229b9e766cd7 · outbound

This paper cites Schmelzer, R.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Schmelzer, R

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.686735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 966d70ed-5a0b-46cc-8eec-63687788d951 · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.653401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5ae4e258-5657-4035-b2f7-79af9d407fc1 · outbound

This paper cites Thévenin, N.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Thévenin, N

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.711806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0dd96d66-5d58-4d88-881e-f97096c5f65f · outbound

This paper cites Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl

Reference 64

Resolution: verified exact; local_arxiv, observed 2026-07-09T21:46:34.590197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a1683ad9-a2b0-4bb8-a637-866ed805a380 · outbound

This paper cites Metropolis, A.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Metropolis, A

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.708088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5e74ccd4-a7c5-4c05-9588-526601e75b59 · outbound

This paper cites doi:10.1098/rstl.1763.0053 , urldate =.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence doi:10.1098/rstl.1763.0053 , urldate =

Reference 66

Resolution: metadata mismatch; arxiv_id, observed 2026-07-09T21:46:34.593487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e94994de-7f52-4150-a2ec-48cc808182f7 · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.690937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2fc60450-5041-46ad-83b6-fc988e04d342 · outbound

This paper cites MCMC using Hamiltonian dynamics.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence MCMC using Hamiltonian dynamics

Reference 68

Resolution: verified exact; local_arxiv, observed 2026-07-09T21:46:34.602590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d48d74dd-3561-4111-b49a-ec78519968f9 · outbound

This paper cites Abril-Pla, V.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Abril-Pla, V

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-07-09T21:46:34.737254Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eb1c3e81-edce-4cfb-b773-bf7f1bbd45b6 · outbound

This paper cites Golub, Michael Heath, and Grace Wahba.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Golub, Michael Heath, and Grace Wahba

Reference 70

Resolution: metadata mismatch; arxiv_id, observed 2026-07-09T21:46:34.551908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ce6db5d9-e3a8-45cf-b5c8-f1dfbaf1d265 · outbound

This paper cites Shukla, P.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Shukla, P

Reference 71

Resolution: verified exact; doi, observed 2026-07-09T21:46:34.552608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f838411b-8cfb-47ad-8f41-a1f8fef5576c · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Adam: A Method for Stochastic Optimization

Reference 72

Resolution: verified exact; local_arxiv, observed 2026-07-09T21:46:34.596864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c37d4ec1-74da-48ad-a698-908dc5672235 · outbound

This paper cites an unresolved cited work.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Unresolved cited work

Reference 73

Resolution: unresolved; raw_fallback, observed 2026-07-09T21:46:34.755307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 76608982-fc12-461e-b2aa-0a6826dd04b1 · outbound

This paper cites Learning in PINNs: Phase transition, total diffusion, and generalization.

Learning Turbulence Closures with Physics-Informed Neural Networks for the Rayleigh-Taylor Transition to Turbulence Learning in PINNs: Phase transition, total diffusion, and generalization

Reference 74

Resolution: verified exact; local_arxiv, observed 2026-07-09T21:46:34.600002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers