Paper Citation Record · LEDGER

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws

As of 14 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2607.20541.

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

pith.paper-citation-record.v1
2607.20541 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T07:31:25.892078Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

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

47 of 47 outbound references displayed

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External citation measurements

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Outbound references

Observation a2cc49d9-3d4f-4c1a-9296-2ff44fd68ec7 · outbound

This paper cites , title =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws , title =

Reference 1

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Observation 396bd55a-1909-4207-a60f-31134352b13e · outbound

This paper cites , title =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws , title =

Reference 2

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Observation 2251b2dd-e5f1-462b-83ce-df0e592d739b · outbound

This paper cites SIAM Review , volume =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws SIAM Review , volume =

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:22.266998Z

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Observation 92621db1-8c6c-408f-9510-83f7496519e6 · outbound

This paper cites an unresolved cited work.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Unresolved cited work

Reference 4

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Observation 1398650d-a41c-47b2-b4e7-a43cb60233f1 · outbound

This paper cites , title =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws , title =

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:22.373431Z

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Observation 80e2cd0b-b3a0-4a8f-976c-e30b94969539 · outbound

This paper cites and Rascle, M.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws and Rascle, M

Reference 6

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Observation 6049d6d9-2f1d-4a23-b717-2f79817929b6 · outbound

This paper cites Physica A: Statistical Mechanics and its Applications , volume =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Physica A: Statistical Mechanics and its Applications , volume =

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:22.546283Z

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Observation e6547daf-b180-42e7-bc8b-6909aea46945 · outbound

This paper cites Front Tracking for Hyperbolic Conservation Laws , publisher =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Front Tracking for Hyperbolic Conservation Laws , publisher =

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:22.607032Z

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Observation 58c39534-8681-4dbc-868e-fccf81bcc1ca · outbound

This paper cites Journal of Computational Physics , volume =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Journal of Computational Physics , volume =

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:22.699896Z

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Observation b4d3931c-fec7-4b6c-b27b-1c4a81be6994 · outbound

This paper cites Variational Physics-Informed Neural Networks For Solving Partial Differential Equations.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Variational Physics-Informed Neural Networks For Solving Partial Differential Equations

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:22.794518Z

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Observation a5e44dd4-0854-48f3-8101-1a1d967abf7c · outbound

This paper cites and Lu, Lu and Perdikaris, Paris and Wang, Sifan and Yang, Liu , title =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws and Lu, Lu and Perdikaris, Paris and Wang, Sifan and Yang, Liu , title =

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:22.857548Z

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Observation deabccbb-329c-439f-9032-905ffe0d7230 · outbound

This paper cites 2026 , eprint =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws 2026 , eprint =

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:22.946172Z

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Observation d0cddf23-fe35-4f49-b1bf-663ef3161696 · outbound

This paper cites Nature Machine Intelligence , volume =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Nature Machine Intelligence , volume =

Reference 13

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Observation 328358b8-6041-4317-ac98-9f5261950ff9 · outbound

This paper cites International Conference on Learning Representations , year =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws International Conference on Learning Representations , year =

Reference 14

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Observation cc75a4dc-3dbe-482d-b68a-1e03ee485f31 · outbound

This paper cites Journal of Machine Learning Research , volume =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Journal of Machine Learning Research , volume =

Reference 15

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Observation d7060f68-ee0b-42aa-ac45-8b58c0d37f70 · outbound

This paper cites ACM / IMS Journal of Data Science , volume =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws ACM / IMS Journal of Data Science , volume =

Reference 16

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Observation 418c5e32-afea-4536-b3ea-7cb41888df68 · outbound

This paper cites ICLR Workshop on Integration of Deep Neural Models and Differential Equations , year =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws ICLR Workshop on Integration of Deep Neural Models and Differential Equations , year =

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:23.364465Z

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Observation 741699f7-b658-489b-87f7-b94510be7178 · outbound

This paper cites Multipole Graph Neural Operator for Parametric Partial Differential Equations.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Multipole Graph Neural Operator for Parametric Partial Differential Equations

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:23.429918Z

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Observation 7a4f24b9-99c7-4ae7-bcc6-2b1a087805c4 · outbound

This paper cites Computer Methods in Applied Mechanics and Engineering , volume =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Computer Methods in Applied Mechanics and Engineering , volume =

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:23.527929Z

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Observation 66ac2d1f-2649-49ed-9dd1-0759a7629f99 · outbound

This paper cites International Conference on Learning Representations , year =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws International Conference on Learning Representations , year =

Reference 20

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Observation 2e9a29e1-f08b-4d0d-aeb8-d6696149d1e2 · outbound

This paper cites and Welling, Max , title =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws and Welling, Max , title =

Reference 21

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Observation 27e1fb9d-69bd-45d9-be0b-34b24ee63680 · outbound

This paper cites Finite Volume Informed Graph Neural Network for Myocardial Perfusion Simulation , booktitle =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Finite Volume Informed Graph Neural Network for Myocardial Perfusion Simulation , booktitle =

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:23.773073Z

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Observation 65d2def0-f0be-47db-85e6-4bff7e5521f2 · outbound

This paper cites Graph Attention Networks.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Graph Attention Networks

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:23.860398Z

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Observation 564e9553-b2e1-411d-9505-200c687cf9b3 · outbound

This paper cites Konstantin and Bronstein, Michael M.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Konstantin and Bronstein, Michael M

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:23.928322Z

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Observation ee28226e-fe84-401d-b409-5e4fb2b470fe · outbound

This paper cites 2023 , eprint =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws 2023 , eprint =

Reference 25

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Observation 98829c89-4dda-414b-93cb-596e21f599ef · outbound

This paper cites On the under-reaching phenomenon in message passing neural.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws On the under-reaching phenomenon in message passing neural

Reference 26

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Observation 0a49925e-324b-428f-8794-0afa2d4264a7 · outbound

This paper cites International Conference on Machine Learning , pages =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws International Conference on Machine Learning , pages =

Reference 27

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Observation 8d35d64b-b853-4016-8af3-5d151f8557e7 · outbound

This paper cites Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws , booktitle =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws , booktitle =

Reference 28

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Observation b7942dbb-fb53-424d-a51f-c543e487d595 · outbound

This paper cites Approximating Numerical Fluxes Using Fourier Neural Operators for Hyperbolic Conservation Laws.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Approximating Numerical Fluxes Using Fourier Neural Operators for Hyperbolic Conservation Laws

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:24.370630Z

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Observation 5adb435a-89e0-41ca-8cca-9a2d83dd0cda · outbound

This paper cites GoRINNs: Godunov-Riemann Informed Neural Networks for Learning Hyperbolic Conservation Laws.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws GoRINNs: Godunov-Riemann Informed Neural Networks for Learning Hyperbolic Conservation Laws

Reference 30

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Observation caf78535-cc14-4c3c-852a-80cc88d4fb1b · outbound

This paper cites Deep learning of first-order nonlinear hyperbolic conservation law solvers , journal =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Deep learning of first-order nonlinear hyperbolic conservation law solvers , journal =

Reference 31

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Observation c860a655-c907-49a5-b753-ccdb05aff416 · outbound

This paper cites International Conference on Learning Representations (ICLR) , year =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws International Conference on Learning Representations (ICLR) , year =

Reference 32

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Observation 75b5383c-362f-4132-afc8-b7860d42996d · outbound

This paper cites A neural network method for scalar conservation laws with convergence rates for shock-wave solutions.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws A neural network method for scalar conservation laws with convergence rates for shock-wave solutions

Reference 33

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Observation df7ccae7-6825-4a2d-80e2-ef23202a315f · outbound

This paper cites and Manickam, Indu and Trask, Nathaniel A.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws and Manickam, Indu and Trask, Nathaniel A

Reference 34

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This paper cites Journal of Computational Physics , volume =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Journal of Computational Physics , volume =

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:24.874063Z

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Observation 6785cfc0-326b-4a67-944e-5e7eea414435 · outbound

This paper cites and Azizzadenesheli, Kamyar , title =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws and Azizzadenesheli, Kamyar , title =

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:24.974175Z

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Observation 8bb1a89c-99b6-4b5d-8439-ffc7ef1d5433 · outbound

This paper cites Advances in Neural Information Processing Systems , year =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Advances in Neural Information Processing Systems , year =

Reference 37

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Observation 74245ef6-0c70-4f52-afdb-a34262c30ed5 · outbound

This paper cites IMA Journal of Numerical Analysis , volume =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws IMA Journal of Numerical Analysis , volume =

Reference 38

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This paper cites SIAM Journal on Numerical Analysis , volume =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws SIAM Journal on Numerical Analysis , volume =

Reference 39

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Observation 350f94f8-b6c4-4440-80a2-132533e3d6e5 · outbound

This paper cites Finite Element Operator Network for Solving Elliptic-type parametric PDEs.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Finite Element Operator Network for Solving Elliptic-type parametric PDEs

Reference 40

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Observation f0e4334e-a76f-49ec-9e1a-fcd331b16d55 · outbound

This paper cites DGNN: A Neural PDE Solver Induced by Discontinuous Galerkin Methods.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws DGNN: A Neural PDE Solver Induced by Discontinuous Galerkin Methods

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:25.327104Z

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Observation 979a82aa-1c44-4665-9285-58a3e9aed268 · outbound

This paper cites and Canesse, Alexi and Delle Monache, Maria Laura and Drieux, Martin and Fu, Zhe and Lichtl.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws and Canesse, Alexi and Delle Monache, Maria Laura and Drieux, Martin and Fu, Zhe and Lichtl

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:25.414288Z

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Observation b0280576-63f8-4646-a2db-fc4d09394c4a · outbound

This paper cites Journal of Computational Physics , volume =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Journal of Computational Physics , volume =

Reference 43

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Observation 9d10d26a-6504-4d1b-b2b4-450f55b4c12b · outbound

This paper cites Journal of Computational and Applied Mathematics , volume =.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Journal of Computational and Applied Mathematics , volume =

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-02T07:31:25.540223Z

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Observation 909e0515-9a20-403f-a5b6-23443fdb914a · outbound

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HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws and Funke, Simon W

Reference 45

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Observation 630a649c-4593-4c55-b509-454db47384a0 · outbound

This paper cites and Dargaville, Steven and Pain, Christopher C.

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws and Dargaville, Steven and Pain, Christopher C

Reference 46

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Observation d8a7214e-ac27-4d26-af35-267b60867a08 · outbound

This paper cites Gaussian Error Linear Units (GELUs).

HypNO: A Graph-Based Neural Operator with Physics-Informed Message Passing for Hyperbolic Conservation Laws Gaussian Error Linear Units (GELUs)

Reference 47

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