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Paper Citation Record · LEDGER

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates

As of 9 August 2026, this Paper Citation Record lists 81 of 81 outbound references and 1 inbound Pith citation observation for arXiv:2506.05513.

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

pith.paper-citation-record.v1
2506.05513 v1

Coverage vector

measured 81 of 81 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:30:13.789264Z

measured 82 of 82 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-30T16:23:26.962085Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

81 of 81 outbound references displayed

  • verified exact1
  • verified fuzzy57
  • unresolved23
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3a3099e3-cc1c-4cb7-b851-df712ee7d4b4 · outbound

This paper cites Computational design of the basic dynamical processes of the ucla general circulation model.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Computational design of the basic dynamical processes of the ucla general circulation model

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation baedcf3f-4c88-4a54-8cab-e58837a2c1de · outbound

This paper cites an unresolved cited work.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Unresolved cited work

Reference 2

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

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Observation 0bc6d075-38ef-4852-8d27-2b885d0c40c6 · outbound

This paper cites an unresolved cited work.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Unresolved cited work

Reference 3

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Observation bc595ae4-b163-499d-8866-e302ea9315e2 · outbound

This paper cites M., Turner, R.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates M., Turner, R

Reference 4

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

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Observation 5882ec3b-4929-4f2e-8c5b-64b575ad0941 · outbound

This paper cites Enforcing analytic constraints in neural networks emulating physical systems.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Enforcing analytic constraints in neural networks emulating physical systems

Reference 5

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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.

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Observation e3f977b9-218d-4123-ae8c-022e682fe058 · outbound

This paper cites Spherical fourier neural operators: Learning stable dynamics on the sphere.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Spherical fourier neural operators: Learning stable dynamics on the sphere

Reference 6

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no resolver link, observed 2026-08-07T10:30:12.577173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1db48b7d-1048-4bee-af21-b5e2f2806b2a · outbound

This paper cites J., and Welling, M.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates J., and Welling, M

Reference 7

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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.

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Observation 9b6fcb06-3ec0-4f3b-99af-c1b2268e5981 · outbound

This paper cites an unresolved cited work.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Unresolved cited work

Reference 8

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

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Observation 4dae8aec-7958-423e-8b10-1cc8e0dc7fc6 · outbound

This paper cites E., and Welling, M.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates E., and Welling, M

Reference 9

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

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Observation 5fceb3a1-c0af-49d2-8859-5466ddf49315 · outbound

This paper cites R., Gupta, R., Magee, A.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates R., Gupta, R., Magee, A

Reference 10

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

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Observation 157a03cc-1077-40db-9827-78ec4e1fcbeb · outbound

This paper cites A program to build e (n)-equivariant steerable cnns.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates A program to build e (n)-equivariant steerable cnns

Reference 11

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

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Observation dd1e76d5-4464-4254-8fd3-67fbf7b2e665 · outbound

This paper cites an unresolved cited work.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Unresolved cited work

Reference 12

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

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Observation 0789a90f-d324-455e-aaef-2316e99a8d93 · outbound

This paper cites N., and Ma, J.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates N., and Ma, J

Reference 13

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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.

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Observation 9233dfc4-d90d-47f8-8841-fdf05b129299 · outbound

This paper cites and Welling, M.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates and Welling, M

Reference 14

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

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Observation 79b5e36a-30cd-4b61-b342-7fc7d1c64764 · outbound

This paper cites Gauge equivariant convolutional networks and the icosahedral cnn.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Gauge equivariant convolutional networks and the icosahedral cnn

Reference 15

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no resolver link, observed 2026-08-07T10:30:12.637926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 49224cd8-9ec6-4e68-bf09-bf97ac76cbc3 · outbound

This paper cites S., Geiger, M., K \"o hler, J., and Welling, M.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates S., Geiger, M., K \"o hler, J., and Welling, M

Reference 16

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no resolver link, observed 2026-08-07T10:30:12.644586Z

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Observation a6534924-5a52-4df7-815e-bc8bbd1c2b40 · outbound

This paper cites Lagrangian Neural Networks.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Lagrangian Neural Networks

Reference 17

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no resolver link, observed 2026-08-07T10:30:12.651390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 302277ff-dbdd-4055-85ac-70df8753ec33 · outbound

This paper cites Gauge equivariant mesh cnns: Anisotropic convolutions on geometric graphs.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Gauge equivariant mesh cnns: Anisotropic convolutions on geometric graphs

Reference 18

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

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Observation 8cc34532-9e4d-49fd-a39c-e59a7b365cb3 · outbound

This paper cites S., Manikin, G.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates S., Manikin, G

Reference 19

Resolution
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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.

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Observation 79beffc5-0d48-4582-8b3d-6dc91e862a75 · outbound

This paper cites Learning so (3) equivariant representations with spherical cnns.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Learning so (3) equivariant representations with spherical cnns

Reference 20

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

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Observation ee7b22e4-b7e0-48d7-bb45-320984fe9148 · outbound

This paper cites General covariance data augmentation for neural pde solvers.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates General covariance data augmentation for neural pde solvers

Reference 21

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

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Observation 201e37e3-d830-4da8-8190-dfc51c918ebf · outbound

This paper cites H., Peri \'c , M., and Street, R.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates H., Peri \'c , M., and Street, R

Reference 22

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

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Observation 201159a6-62e2-4d20-aa4a-9ae5a208c834 · outbound

This paper cites Directional message passing for molecular graphs.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Directional message passing for molecular graphs

Reference 23

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

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Observation 5a4d45a3-2bbb-4346-bace-0703df9948f7 · outbound

This paper cites Learning to optimize multigrid pde solvers.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Learning to optimize multigrid pde solvers

Reference 24

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

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Observation af341305-62d1-479c-adb1-fdc07e22de69 · outbound

This paper cites Hamiltonian neural networks.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Hamiltonian neural networks

Reference 25

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

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Observation dd1c92f8-956d-48cb-9c5d-8262be20bb53 · outbound

This paper cites an unresolved cited work.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Unresolved cited work

Reference 26

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

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Observation 6ec65ab7-8c42-4786-9cc8-3f4cf7f5b3d6 · outbound

This paper cites Group equivariant fourier neural operators for partial differential equations.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Group equivariant fourier neural operators for partial differential equations

Reference 27

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raw_fallback, observed 2026-08-07T10:30:14.522089Z

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

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Observation db7083c3-efa0-45e3-ac07-947c0daf7b64 · outbound

This paper cites and Thuerey, N.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates and Thuerey, N

Reference 28

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

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Observation 4d81f30c-282f-4223-9ad9-ce1a61c83908 · outbound

This paper cites and Mitsume, N.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates and Mitsume, N

Reference 29

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raw_fallback, observed 2026-08-07T10:30:14.499458Z

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.

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Observation 1c61652c-a6dd-4b26-a6a1-fef082c7ad0a · outbound

This paper cites Learning neural pde solvers with convergence guarantees.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Learning neural pde solvers with convergence guarantees

Reference 30

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raw_fallback, observed 2026-08-07T10:30:14.487778Z

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

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Observation f62caf99-1564-4d97-9a9c-cd8111435032 · outbound

This paper cites and Greenberg, D.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates and Greenberg, D

Reference 31

Resolution
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raw_fallback, observed 2026-08-07T10:30:14.475404Z

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.

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Observation fbf710a8-c9a8-4dca-a14e-43c1d9a0840d · outbound

This paper cites Openfoam: Open source cfd in research and industry.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Openfoam: Open source cfd in research and industry

Reference 32

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raw_fallback, observed 2026-08-07T10:30:14.464311Z

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.

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Observation 6434e390-ff90-4c7e-ac52-9e8483264202 · outbound

This paper cites u ggemann, N., Chegini, F., Cr \.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates u ggemann, N., Chegini, F., Cr \

Reference 33

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raw_fallback, observed 2026-08-07T10:30:14.451899Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.762290Z digest=sha256:df3e5e1aeba352892aecdde0454d8bcffb67069a03575f373c20ed1cad783e8a

Observation b72d73cd-de97-434c-9995-a70f4fa4bdfd · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Adam: A Method for Stochastic Optimization

Reference 34

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unresolved
no resolver link, observed 2026-08-07T10:30:12.769533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:30:12.769533Z digest=sha256:9ac4a4f9c887b0585eb8699f77b0dafe1f3711be5bc307d5004888b68fcc7c35

Observation cafa213c-a74f-44c1-8731-712491fea8e5 · outbound

This paper cites M., Wessels, D., Valperga, R., Papa, S., Sonke, J.-J., Bekkers, E.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates M., Wessels, D., Valperga, R., Papa, S., Sonke, J.-J., Bekkers, E

Reference 35

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raw_fallback, observed 2026-08-07T10:30:14.439333Z

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.

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Observation f4cacd03-fbb5-4938-8584-5fcd198f1417 · outbound

This paper cites A., Alieva, A., Wang, Q., Brenner, M.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates A., Alieva, A., Wang, Q., Brenner, M

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.427502Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.783782Z digest=sha256:634941716f2c109fecae4ddad968261350cd60b2cf3935d09e2940f9c6aff5e4

Observation 6aac759d-3269-4186-bee5-040f32da4520 · outbound

This paper cites o wer, M., Lottes, J., Rasp, S., D \.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates o wer, M., Lottes, J., Rasp, S., D \

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.415723Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.790645Z digest=sha256:86bc0280c3bd16ed622b5db5ec96cbc2890984715ef27cde0b6aa7f3ba31765a

Observation efd7689a-017e-496b-bbd8-21abccf90689 · outbound

This paper cites Benchmarking autoregressive conditional diffusion models for turbulent flow simulation.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Benchmarking autoregressive conditional diffusion models for turbulent flow simulation

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.403737Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.797446Z digest=sha256:9f9596174754b350537e1f5bc3e05d4ec3dfcc3555f325a03b68ad67ae4fef1c

Observation 0e9425c4-3eaf-4e48-b76d-2552a2abe19a · outbound

This paper cites H., Lorenz, S., Gutjahr, O., Haak, H., Linardakis, L., Mehlmann, C., Mikolajewicz, U., Notz, D., et al.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates H., Lorenz, S., Gutjahr, O., Haak, H., Linardakis, L., Mehlmann, C., Mikolajewicz, U., Notz, D., et al

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.392955Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.804499Z digest=sha256:cfc9ed8c187eac7534db9efba06285a1a5a7392581788240be33f57a849eaf29

Observation c97d56e0-b124-4aff-b0a7-dff10f7f451c · outbound

This paper cites B., Azizzadenesheli, K., Bhattacharya, K., Stuart, A., Anandkumar, A., et al.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates B., Azizzadenesheli, K., Bhattacharya, K., Stuart, A., Anandkumar, A., et al

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.380693Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.811674Z digest=sha256:f2c0183530ce14cd2eb54e684d410bdf3b1dae1fa42e29aaa53547d19cf1848a

Observation 70d784ae-727f-4b75-9cb9-7384e5d62343 · outbound

This paper cites Long-term predictions of turbulence by implicit u-net enhanced fourier neural operator.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Long-term predictions of turbulence by implicit u-net enhanced fourier neural operator

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.369013Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.818782Z digest=sha256:51e5f0db1dc948e1d3507dd1b830e9e709dc0e5f5a70a320a574e906660b5c3d

Observation 96466872-52d6-47d6-bd28-5072aedc4e29 · outbound

This paper cites A., and Cantwell, C.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates A., and Cantwell, C

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.355389Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.826095Z digest=sha256:f7187a790fd2593d32c1741f4b447bf1d333cd53eaef78190d8f402c8e5a7e48

Observation 81de23a2-aa46-4d8d-8ea0-23d4c48ce4b9 · outbound

This paper cites Pde-refiner: Achieving accurate long rollouts with neural pde solvers.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Pde-refiner: Achieving accurate long rollouts with neural pde solvers

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.342367Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.832882Z digest=sha256:8dff0b43e511b000a661055026607ccc886bdc24ca901b2c57a1c57d1f6c7e04

Observation abb759a6-8a71-498d-b90f-4d75ed664482 · outbound

This paper cites How temporal unrolling supports neural physics simulators.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates How temporal unrolling supports neural physics simulators

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.329750Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.843004Z digest=sha256:8d368a04e6b6846ab70b2472d4d73286a988474badce72d90b630130b225d223

Observation 9aade8b4-dd6a-408a-afd8-a452c1d2baba · outbound

This paper cites Pde-net 2.0: Learning pdes from data with a numeric-symbolic hybrid deep network.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Pde-net 2.0: Learning pdes from data with a numeric-symbolic hybrid deep network

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.317791Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.849175Z digest=sha256:0588a665b5e673fd7315d4aefe9e9ee771d8077b035bb3c056a0739d9f37c117

Observation e36655e7-b2ad-4556-acb8-96411f702823 · outbound

This paper cites G., Paronuzzi, S., Peltier, M., Person, R., Rousset, C., Rynders, S., Samson, G., Téchené, S., Vancoppenolle, M., and Wilson, C.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates G., Paronuzzi, S., Peltier, M., Person, R., Rousset, C., Rynders, S., Samson, G., Téchené, S., Vancoppenolle, M., and Wilson, C

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.305054Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.856445Z digest=sha256:76231089a3fc316694d17387ca975fa15fe836f31856bb822cbc3c136797d371

Observation e5705540-c000-43c9-b720-bdca29adb27d · outbound

This paper cites Nemo ocean engine reference manual.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Nemo ocean engine reference manual

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T10:30:12.863750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:30:12.863750Z digest=sha256:332ec28578267644ca7ca44a448c6aa7a10f9eafe54dd29157a8668fbdf0b6b7

Observation a8bbe180-16cd-40dd-afcc-645215a76516 · outbound

This paper cites Combining model and geostationary satellite data to reconstruct hourly sst field over the mediterranean sea.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Combining model and geostationary satellite data to reconstruct hourly sst field over the mediterranean sea

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.293945Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.870618Z digest=sha256:40dcc9189e96ca9fb42a852a8abb24021237b3001e839838d91c1f26b9535d9f

Observation 92cccf1c-690b-4963-8634-746b5bdb50f6 · outbound

This paper cites and Hakim, A.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates and Hakim, A

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.281747Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.877756Z digest=sha256:ccab1d9679c9df192dcf8d3ab0559260672975391e148a46b0eb79fe70e700cb

Observation 6f454651-206d-418c-abb2-68b2dea69dc6 · outbound

This paper cites Physics-constrained Unsupervised Learning of Partial Differential Equations using Meshes.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Physics-constrained Unsupervised Learning of Partial Differential Equations using Meshes

Reference 50

Resolution
verified exact
local_arxiv, observed 2026-08-07T10:30:13.875291Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.884312Z digest=sha256:1f66950302d4853474d62a480740e527590e3c5ef198b40070e5c36c3eaf7a7a

Observation 5a848c93-e700-4006-9843-fb6459f9105b · outbound

This paper cites Embedding Hard Physical Constraints in Neural Network Coarse-Graining of 3D Turbulence.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Embedding Hard Physical Constraints in Neural Network Coarse-Graining of 3D Turbulence

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T10:30:12.891465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:30:12.891465Z digest=sha256:fba25587a8f67bf261724c3bcab63c0c9579caf14947c428e5cba62d792700eb

Observation 9b9d1db5-eb43-4715-9129-343d32e4f599 · outbound

This paper cites K., and Grover, A.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates K., and Grover, A

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.271231Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.898766Z digest=sha256:288f37607afc6a1703c2485b6a92e092179546d0c80865b20857b5f71baf4f14

Observation 48416ddb-4d08-488e-af9f-ac29f03d9b40 · outbound

This paper cites Invariante variationsprobleme.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Invariante variationsprobleme

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.259941Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.905476Z digest=sha256:3ab3038edcf28bfbd7aac5e5ab22c842c80bc5788f68f66f08a970250611ca5c

Observation 9071cb97-2fc4-46ca-b5d2-97fb52edce08 · outbound

This paper cites an unresolved cited work.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Unresolved cited work

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-07T10:30:12.912396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:30:12.912396Z digest=sha256:66ead88b640a14b8ba736f3821ae5c02a068da40d3a35b4bb323872bdd5cdc13

Observation 009e5016-3a4f-4753-8e33-f6dc94a626ea · outbound

This paper cites Convolutional neural operators for robust and accurate learning of pdes.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Convolutional neural operators for robust and accurate learning of pdes

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.242441Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.919444Z digest=sha256:8bc142d55c90b6e7dd74aafa79716ecb04f45751ef8b1215ebec04babf60a3de

Observation 60653113-7976-4041-bd8c-6015a4d90106 · outbound

This paper cites S., Jia, X., Willard, J., Appling, A.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates S., Jia, X., Willard, J., Appling, A

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.230250Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.926607Z digest=sha256:76fe5bd24d6b87c684be831ac1833022ea9421438a17f9d42ddeb501be017ed2

Observation 21ba133e-9340-4460-83e2-5241675498fc · outbound

This paper cites and Valiquette, F.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates and Valiquette, F

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.218322Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.933380Z digest=sha256:63985cb2630c8815a1c4341466fafec5efc8dd3f6dfb456590039b8ec28375e8

Observation 21554504-d1b1-43d1-8473-d6585788f0a6 · outbound

This paper cites an unresolved cited work.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Unresolved cited work

Reference 58

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:30:14.205579Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.940531Z digest=sha256:4803ed5592658d8ba5382655e4596fc182a4040af46420e8b4fab043ce5f1680

Observation 45301de0-1161-492e-8204-9993c2a89bfd · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates U-net: Convolutional networks for biomedical image segmentation

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-07T10:30:12.947257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:30:12.947257Z digest=sha256:e5e6cad517e3478fde3a00e47ed67060eaf0e0d25ee45b1c762689cb00a2e136

Observation b83fa8b2-e553-47d5-b0e7-bcf38c580d30 · outbound

This paper cites Clifford group equivariant neural networks.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Clifford group equivariant neural networks

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.189199Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.954497Z digest=sha256:3ebf59322a9a33bd139aef2d676d1faa32055e12450d8128f36b1b294ff9a29d

Observation 9bddb6d3-7e8a-4165-8b38-594c3d71987b · outbound

This paper cites Learning to simulate complex physics with graph networks.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Learning to simulate complex physics with graph networks

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.178796Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.961486Z digest=sha256:68879862ed5802c099cdeafeaf95f05f8bd6ad81abd540a90b10704d4d3893a6

Observation 185883a4-3c9c-46f3-b2fc-a4001b3c05af · outbound

This paper cites DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T10:30:12.968735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:30:12.968735Z digest=sha256:69babecb19e63734c09b34ce85a03ecbd845b8b98d5454c4fd6f23d0ee359fe7

Observation 53ab7782-02d8-416b-b3cb-7e95ac06b5cd · outbound

This paper cites M., Portegies, J., Bekkers, E.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates M., Portegies, J., Bekkers, E

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.167644Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.975365Z digest=sha256:41624d1080caa3c11f520923bddf184ba3ca15a1455219eca1c48f4ee0c9b160

Observation c1ab512a-8a92-4004-b517-f824004cee54 · outbound

This paper cites The shifted boundary method for hyperbolic systems: Embedded domain computations of linear waves and shallow water flows.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates The shifted boundary method for hyperbolic systems: Embedded domain computations of linear waves and shallow water flows

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.155725Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.982424Z digest=sha256:26e392871539d60d5c929b15b585f548b4f5033bf3799dfb79c9883351030ef3

Observation b99d21f1-c84f-454f-9fc7-3c39b0fb4579 · outbound

This paper cites an unresolved cited work.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Unresolved cited work

Reference 65

Resolution
unresolved
raw_fallback, observed 2026-08-07T10:30:14.144211Z

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.

source=arxiv_source observed=2026-08-07T10:30:12.991023Z digest=sha256:f7431741e2f4e5a2e3e2eafa727d5f492c61b040f7711f8b0f14fdbed8e7aec4

Observation e49a1064-0fec-47a4-8623-9305aaf36eca · outbound

This paper cites Learned Coarse Models for Efficient Turbulence Simulation.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Learned Coarse Models for Efficient Turbulence Simulation

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-07T10:30:12.998844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:30:12.998844Z digest=sha256:fac6240892f3f35212c32984447f6e245f28b08269229cdf7f7d185a777f0fe1

Observation 2788426b-8314-4eda-a961-673a59f1b286 · outbound

This paper cites M., Tomida, K., White, C.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates M., Tomida, K., White, C

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-07T10:30:13.082112Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:30:13.082112Z digest=sha256:23b3847e3966a2f2230e5444de3e957a5fc6f98420011c2458cc24e377f2e9a9

Observation 8fbe54ae-4504-48f6-9c6d-6a8ebf170687 · outbound

This paper cites A neural pde solver with temporal stencil modeling.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates A neural pde solver with temporal stencil modeling

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.133280Z

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.

source=arxiv_source observed=2026-08-07T10:30:13.431644Z digest=sha256:891abce14e9ce74a98200e0a38a25381154d9697113f65453150a11b2faf512b

Observation 796ac7ef-0137-46ca-8e09-af5dc239b684 · outbound

This paper cites Pdebench: An extensive benchmark for scientific machine learning.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Pdebench: An extensive benchmark for scientific machine learning

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.121448Z

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.

source=arxiv_source observed=2026-08-07T10:30:13.636162Z digest=sha256:b3b31ae113a23dc462bb47a98d79222f05c3d2d0faea92ab3d59a1629286f8d1

Observation aec163db-22fa-48aa-b9ac-5e9e14d6c72f · outbound

This paper cites Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-07T10:30:13.716882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:30:13.716882Z digest=sha256:0e4a01f61ddd3e303b96e3747e42658c0719ce91b1044042efb6878957ee1840

Observation fdaa3761-f805-4229-bdf4-18b02829d585 · outbound

This paper cites Accelerating eulerian fluid simulation with convolutional networks.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Accelerating eulerian fluid simulation with convolutional networks

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:30:14.109421Z

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.

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This paper cites P., Galletti, G., Brandstetter, J., Adami, S., and Adams, N.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates P., Galletti, G., Brandstetter, J., Adami, S., and Adams, N

Reference 72

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

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Observation 8d3a42b5-ff1a-4dba-8477-5528d6d863c2 · outbound

This paper cites an unresolved cited work.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Unresolved cited work

Reference 73

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

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Observation bf6babf0-8976-4440-a56e-4d10ededf875 · outbound

This paper cites and Chakraborty, S.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates and Chakraborty, S

Reference 74

Resolution
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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.

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Observation 7f2387c8-189e-425a-b769-a7abd1266a09 · outbound

This paper cites R., Holl, P., and Thuerey, N.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates R., Holl, P., and Thuerey, N

Reference 75

Resolution
verified fuzzy
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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.

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Observation 4974ae35-9462-404e-9357-625c23bd2ae9 · outbound

This paper cites S., Linmans, J., Winkens, J., Cohen, T., and Welling, M.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates S., Linmans, J., Winkens, J., Cohen, T., and Welling, M

Reference 76

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

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Observation 63b06909-892d-434b-a07e-2aa0090bb2ca · outbound

This paper cites Learning incompressible fluid dynamics from scratch-towards fast, differentiable fluid models that generalize.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Learning incompressible fluid dynamics from scratch-towards fast, differentiable fluid models that generalize

Reference 77

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

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Observation 2fbc5f7b-c7bd-4ce1-ba94-86c55d61f5fe · outbound

This paper cites Incorporating symmetry into deep dynamics models for improved generalization.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates Incorporating symmetry into deep dynamics models for improved generalization

Reference 78

Resolution
verified fuzzy
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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.

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Observation 6fa6a7a7-bd58-404e-95b5-e8a729a5d6ba · outbound

This paper cites K., Henn, B., Duncan, J., Brenowitz, N.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates K., Henn, B., Duncan, J., Brenowitz, N

Reference 79

Resolution
verified fuzzy
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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.

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Observation 633fdb46-adaa-4e06-b1d6-55638a7c8fc9 · outbound

This paper cites and Cesa, G.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates and Cesa, G

Reference 80

Resolution
verified fuzzy
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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.

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Observation b1a008d6-9df6-46e6-bba5-c5e51129f771 · outbound

This paper cites write newline.

Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates write newline

Reference 81

Resolution
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Unavailable: canonical work link unavailable.

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Pith citing papers

Observation 29c8536f-1f4f-4d50-a59e-e0f3dd713cba · inbound

No Free Lunch in Flow Surrogates under Time-Varying Boundary Conditions: A Two-Regime Study cites this paper.

No Free Lunch in Flow Surrogates under Time-Varying Boundary Conditions: A Two-Regime Study Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates

Reference 72

Resolution
unresolved
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Unavailable: canonical work link unavailable.

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