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Paper Citation Record · LEDGER

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws

As of 9 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 0 inbound Pith citation observations for arXiv:2607.06587.

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

pith.paper-citation-record.v1
2607.06587 v1

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T19:51:56.544026Z

measured 70 of 70 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

70 of 70 outbound references displayed

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  • verified fuzzy0
  • unresolved43
  • parse uncertain1
  • malformed identifier1
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External citation measurements

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Outbound references

Observation ba0196c1-0025-4e10-9f5d-703e73efafd8 · outbound

This paper cites Parametric airfoil catalog, Part II: G.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Parametric airfoil catalog, Part II: G

Reference 1

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Observation b6985b18-f27c-43de-aafd-4dc6d3707720 · outbound

This paper cites 2017 , publisher=.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws 2017 , publisher=

Reference 2

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Observation fa6ef66b-06dc-44af-b30c-394e2f172305 · outbound

This paper cites 2012 , publisher=.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws 2012 , publisher=

Reference 3

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Observation e10ef5d7-cb76-4077-8225-36a5203be874 · outbound

This paper cites Progress in Aerospace Sciences , year=.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Progress in Aerospace Sciences , year=

Reference 4

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Observation 57047627-dc4e-4c52-8094-383f2f9e5e52 · outbound

This paper cites Scientific Reports , year=.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Scientific Reports , year=

Reference 5

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Observation 5be9f9f3-7108-4192-9cb1-c1d4bf67d19e · outbound

This paper cites , year =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws , year =

Reference 6

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Observation 82caf4ea-45b7-47a2-afb3-8b93cf0267cb · outbound

This paper cites Independent Component Analyses, Wavelets, and Neural Networks , volume=.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Independent Component Analyses, Wavelets, and Neural Networks , volume=

Reference 7

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Observation d7bfef97-8ac9-428d-8057-983bbb104dbf · outbound

This paper cites Aerospace Science and Technology , year=.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Aerospace Science and Technology , year=

Reference 8

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Observation 7b8889f0-b125-4953-a74f-da2009b6aeb8 · outbound

This paper cites 2018 , journal =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws 2018 , journal =

Reference 9

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Observation 46138833-d38a-4c73-ae4b-3131011a0fbc · outbound

This paper cites Super-resolution reconstruction of turbulent flows with machine learning , volume=.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Super-resolution reconstruction of turbulent flows with machine learning , volume=

Reference 10

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Observation 47f2f344-36ba-49c7-a2ea-874d5914297d · outbound

This paper cites A supervised neural network for drag prediction of arbitrary 2D shapes in laminar flows at low Reynolds number , journal =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws A supervised neural network for drag prediction of arbitrary 2D shapes in laminar flows at low Reynolds number , journal =

Reference 11

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Observation 8e61dff6-c757-4ca6-b94e-6a201e213f51 · outbound

This paper cites Journal of Fluid Mechanics , volume=.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Journal of Fluid Mechanics , volume=

Reference 12

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Observation 874e9b03-eec7-499e-8b70-78699bdaf043 · outbound

This paper cites U-net architectures for fast prediction of incompressible laminar flows.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws U-net architectures for fast prediction of incompressible laminar flows

Reference 13

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Observation 83e79c60-b3d5-44f6-80cd-4e9495caf0e9 · outbound

This paper cites Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , pages =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , pages =

Reference 14

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Observation f41e09d9-f88e-499a-8591-485788906d82 · outbound

This paper cites 2017 , journal =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws 2017 , journal =

Reference 15

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Observation f38b6b58-cf9e-40bc-a7bf-2c7cfae74ff1 · outbound

This paper cites 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference , year=.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference , year=

Reference 16

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Observation 0883cb72-c866-4ba6-9abd-14ee6f441de9 · outbound

This paper cites Prediction of aerodynamic flow fields using convolutional neural networks , volume =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Prediction of aerodynamic flow fields using convolutional neural networks , volume =

Reference 17

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Observation 8517032f-8da6-4ca9-883c-2f491e3ce470 · outbound

This paper cites Fast flow field prediction over airfoils using deep learning approach , volume =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Fast flow field prediction over airfoils using deep learning approach , volume =

Reference 18

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Observation e8b16ffd-b148-46e1-b945-bafc0513d952 · outbound

This paper cites Deep Learning Methods for Reynolds-Averaged.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Deep Learning Methods for Reynolds-Averaged

Reference 19

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Observation 02775b2c-a41f-42a8-abb3-aa69ba951468 · outbound

This paper cites Flow field prediction of supercritical airfoils via variational autoencoder based deep learning framework , volume =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Flow field prediction of supercritical airfoils via variational autoencoder based deep learning framework , volume =

Reference 20

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Observation 7637992c-5ae8-41f2-9f30-efbc960ad488 · outbound

This paper cites CNNFOIL: convolutional encoder decoder modeling for pressure fields around airfoils , volume =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws CNNFOIL: convolutional encoder decoder modeling for pressure fields around airfoils , volume =

Reference 21

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Observation 7fae520a-4c84-4b18-aa42-0956de94d083 · outbound

This paper cites A generative deep learning framework for airfoil flow field prediction with sparse data , volume =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws A generative deep learning framework for airfoil flow field prediction with sparse data , volume =

Reference 22

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Observation 985ed1dd-83c9-4621-93be-ffca1d188a1d · outbound

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CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws The Aeronautical Journal (1968) , year=

Reference 23

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Observation a4777f95-ec0d-47ef-bf01-dc2bb63e5d38 · outbound

This paper cites A cost-effective CNN-BEM coupling framework for design optimization of horizontal axis tidal turbine blades.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws A cost-effective CNN-BEM coupling framework for design optimization of horizontal axis tidal turbine blades

Reference 24

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Observation e3254919-92ad-4f19-973a-2cb72ae343c6 · outbound

This paper cites Fast sparse flow field prediction around airfoils via multi-head perceptron based deep learning architecture.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Fast sparse flow field prediction around airfoils via multi-head perceptron based deep learning architecture

Reference 25

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Observation acea1906-8153-4ff7-8fce-c83789cf01fc · outbound

This paper cites A comparative study of learning techniques for the compressible aerodynamics over a transonic RAE2822 airfoil.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws A comparative study of learning techniques for the compressible aerodynamics over a transonic RAE2822 airfoil

Reference 26

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Observation a0028cf1-883a-4d6c-aa22-b96cc553ad58 · outbound

This paper cites Machine learning-based surrogate modeling approaches for fixed-wing store separation.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Machine learning-based surrogate modeling approaches for fixed-wing store separation

Reference 27

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This paper cites U-FNO -- An enhanced Fourier neural operator-based deep-learning model for multiphase flow.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws U-FNO -- An enhanced Fourier neural operator-based deep-learning model for multiphase flow

Reference 28

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Observation ce741224-3780-4e39-9c38-c7387569ce55 · outbound

This paper cites Toward a Better Understanding of Fourier Neural Operators from a Spectral Perspective.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Toward a Better Understanding of Fourier Neural Operators from a Spectral Perspective

Reference 29

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CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws , year =

Reference 30

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CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Communications in Computational Physics , author =

Reference 31

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CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws arXiv.org , author =

Reference 32

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CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Neural fields for rapid aircraft aerodynamics simulations , volume =

Reference 33

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This paper cites X-MeshGraphNet: Scalable Multi-Scale Graph Neural Networks for Physics Simulation.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws X-MeshGraphNet: Scalable Multi-Scale Graph Neural Networks for Physics Simulation

Reference 34

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CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Computers & Fluids , author =

Reference 35

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Observation ebce835b-5e25-4a75-abd6-2c12df916f35 · outbound

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CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Physics of Fluids , author =

Reference 36

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Observation dd6cf5b2-1e3c-46d6-8d6d-9e9ab607a31c · outbound

This paper cites Physics-informed neural networks for solving moving interface flow problems using the level set approach , url =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Physics-informed neural networks for solving moving interface flow problems using the level set approach , url =

Reference 37

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no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:a62f4038c8a74b0181e89ff50caaf5ca46cd67995386c07e0fc1eb53f46e8121

Observation 919eabc6-a0af-4a8b-8862-5a0c322ad90b · outbound

This paper cites NeuralFoil: An Airfoil Aerodynamics Analysis Tool Using Physics-Informed Machine Learning.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws NeuralFoil: An Airfoil Aerodynamics Analysis Tool Using Physics-Informed Machine Learning

Reference 38

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no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:8fb0f9334252cfe395e10c52b1eddf93397a6a8df7aa5ec3acd243658c2d5749

Observation 7998b886-572d-4d72-8c83-379477458b83 · outbound

This paper cites International Mechanical Engineering Congress and Exposition-India , volume=.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws International Mechanical Engineering Congress and Exposition-India , volume=

Reference 39

Resolution
unresolved
no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:6bc5681fd0e04f96ea615f6a9c0235ae3de52d42f724012a0ad66477ef19b2e6

Observation 15df7452-372b-4648-a3b6-41398928be28 · outbound

This paper cites Extended Interface Physics-Informed Neural Networks Method for Moving Interface Problems.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Extended Interface Physics-Informed Neural Networks Method for Moving Interface Problems

Reference 40

Resolution
unresolved
no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:0c68ce626abdb376045a33c2d3ac00bd80c866bf2de8833763f4082123b4700d

Observation 580f0842-f18f-41ba-87a3-9270f4a154bd · outbound

This paper cites Computers & Fluids , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Computers & Fluids , author =

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-07-11T19:58:13.688027Z

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=2026-07-11T19:51:56.544026Z digest=sha256:e0b51cf0412440911b654dbdad40457cda291891cf13d9d815ec3fbb2c63401b

Observation 886c5c79-afc2-4a22-95f1-c719777b49d7 · outbound

This paper cites Heliyon , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Heliyon , author =

Reference 42

Resolution
verified exact
doi, observed 2026-07-11T19:58:13.723251Z

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=2026-07-11T19:51:56.544026Z digest=sha256:35a4eadddadf9de25839801af39379b575c1ad00778b1e3927b00051582f349a

Observation d4cb9ed4-ff31-41f9-8aae-0dcabf6fff0e · outbound

This paper cites Fluids , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Fluids , author =

Reference 43

Resolution
verified exact
doi, observed 2026-07-11T19:58:13.668026Z

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=2026-07-11T19:51:56.544026Z digest=sha256:792d6cc86fe351875d87331c528b7a610bff4af8ba8232dcb95656311132a7ab

Observation 41d7bc84-f554-49fc-beb6-b6c7a2925efb · outbound

This paper cites Journal of Computational Physics , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Journal of Computational Physics , author =

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-07-11T19:58:13.713557Z

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=2026-07-11T19:51:56.544026Z digest=sha256:e435cd0ad49edfeae8f03660b739bc576e0acf7e2e161669c81f6686b864141c

Observation 2d356a0f-1944-4cb9-9f9f-403a9c2cddcf · outbound

This paper cites Physics of Fluids , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Physics of Fluids , author =

Reference 45

Resolution
verified exact
doi, observed 2026-07-11T19:58:13.656600Z

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=2026-07-11T19:51:56.544026Z digest=sha256:327469cf1a3891d00df9d09698db8b32f314f30c62fbc021713dd33a863f257d

Observation 7c78a09e-0527-41ee-a1e1-73173b781436 · outbound

This paper cites Applied Sciences , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Applied Sciences , author =

Reference 46

Resolution
verified exact
doi, observed 2026-07-11T19:58:13.646983Z

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=2026-07-11T19:51:56.544026Z digest=sha256:52a457ef733f49dfde043b0b32007025e419c41716063ca920bb880de24122af

Observation 5aaff1d3-53a6-45bb-b313-731dacf6649d · outbound

This paper cites Aerospace Science and Technology , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Aerospace Science and Technology , author =

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-07-11T19:58:13.742989Z

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=2026-07-11T19:51:56.544026Z digest=sha256:3478aec83311002df4df3b25c057d6c1d0123c93bb71012789591e40fe8649d3

Observation 66292df7-6f16-4bb6-99fe-99a0c78060e8 · outbound

This paper cites AIAA Journal , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws AIAA Journal , author =

Reference 48

Resolution
verified exact
doi, observed 2026-07-11T19:58:13.651784Z

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=2026-07-11T19:51:56.544026Z digest=sha256:f194e39a3fc5f64425ef503936644b01ea14ad91a61821a1fc24bb418858ffae

Observation ba7cb533-6444-4950-9d84-d507d3ef4c31 · outbound

This paper cites Entropy , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Entropy , author =

Reference 49

Resolution
verified exact
doi, observed 2026-07-11T19:58:13.727734Z

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=2026-07-11T19:51:56.544026Z digest=sha256:ffd5640aa5991fffd00ca83ca00749ea864a667c294f36d5c48d1e9279bf3f14

Observation 5d683c5c-437f-40b0-81a5-ecca30e71704 · outbound

This paper cites Applied Sciences , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Applied Sciences , author =

Reference 50

Resolution
verified exact
doi, observed 2026-07-11T19:58:13.718548Z

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=2026-07-11T19:51:56.544026Z digest=sha256:3e793afb1beb27fda0636a8403aa92c89917c8b06eb4112417f76a88732e61ba

Observation f0e2e68c-648d-4d75-a7d0-d78b08ab3b75 · outbound

This paper cites 2024 , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws 2024 , author =

Reference 51

Resolution
parse uncertain
no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:cfc1b1406c7174ce8969dcfe3b6fbed57efd90a3f0c553ba9aef835a6aa65d1f

Observation 8745f37a-596b-4a11-91d1-1371dfa5e668 · outbound

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

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Computer Methods in Applied Mechanics and Engineering , author =

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-07-11T19:58:13.701295Z

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=2026-07-11T19:51:56.544026Z digest=sha256:66235bbfc206cae8ed58061148bea75c96e3b7d2189f729692a4f2c164f4c936

Observation f5b1ecf4-e422-4cb2-ba0a-9f6b1041eb66 · outbound

This paper cites Physics of Fluids , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Physics of Fluids , author =

Reference 53

Resolution
verified exact
doi, observed 2026-07-11T19:58:13.641125Z

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=2026-07-11T19:51:56.544026Z digest=sha256:24f16273324890b9a1735ba4bbdbe11022df606b254a470e226a610abcd8aeee

Observation c8c809f8-c51f-44dd-bf15-93caf41de186 · outbound

This paper cites Physics of Fluids , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Physics of Fluids , author =

Reference 54

Resolution
verified exact
doi, observed 2026-07-11T19:58:13.702942Z

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=2026-07-11T19:51:56.544026Z digest=sha256:c9cb768335834d188f2d89eb0ffde2050170ad2cfab198e5e08f216df02f8f77

Observation 0794d6b9-0353-425b-a5ef-242e3155514d · outbound

This paper cites Physics of Fluids , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Physics of Fluids , author =

Reference 55

Resolution
verified exact
doi, observed 2026-07-11T19:58:13.746061Z

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=2026-07-11T19:51:56.544026Z digest=sha256:de88ce52fd9ff982c5ebcb0f398ac28e6a97e470a66d38dc77d04ebbd4814515

Observation e47fc17f-82de-4415-ac22-3063e8e03890 · outbound

This paper cites Computers & Fluids , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Computers & Fluids , author =

Reference 56

Resolution
verified exact
arxiv_id, observed 2026-07-11T19:58:13.732723Z

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=2026-07-11T19:51:56.544026Z digest=sha256:125964ce00a7251dbfef6d39a49d8c7d0b414641b0b14dc8a598fe9d897980a8

Observation f1bc8baa-fb45-4afb-bb62-1365aef85931 · outbound

This paper cites International Journal for Numerical Methods in Fluids , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws International Journal for Numerical Methods in Fluids , author =

Reference 57

Resolution
verified exact
doi, observed 2026-07-11T19:58:13.660821Z

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=2026-07-11T19:51:56.544026Z digest=sha256:a01d049e4f1c024aebb2d1cb8f977679e5f940e589a8b94f6ff0046beae8797c

Observation 70306e2c-06f6-4710-9170-3fd004ccf868 · outbound

This paper cites SIAM Journal on Scientific Computing , author =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws SIAM Journal on Scientific Computing , author =

Reference 58

Resolution
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no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:ec878e5a23ea2f14b1dd1945a4dbe74f7266987c2dfe18cd76e151b1814e5541

Observation 745d1cb6-09ae-48cf-bbd9-9036f7ac63ce · outbound

This paper cites Energies , volume =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Energies , volume =

Reference 59

Resolution
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no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:475292f57723e64e1e2f54c605c148d98a8d5d2a4d06f76dfaa927527b231d8c

Observation d20e2af1-99ea-4df6-8c64-976acb3c1841 · outbound

This paper cites 30th Aerospace Sciences Meeting and Exhibit , pages=.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws 30th Aerospace Sciences Meeting and Exhibit , pages=

Reference 60

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no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:014f235e3ce82d30c674fcf9609bf627ba13fea05112e0200abd57aafb6bef0f

Observation 8e46fde8-d0ca-433d-9bd3-335f99e8f009 · outbound

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

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Advances in Neural Information Processing Systems , volume=

Reference 61

Resolution
unresolved
no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:91d523256b48d57f158501ba9753d8d153bbfe88e8f15e1a8636ac01a462be4d

Observation 949afec9-d289-4a30-9980-179124d3b004 · outbound

This paper cites and di Bernardo, Mario and Russo, Lucia and Siettos, Constantinos I.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws and di Bernardo, Mario and Russo, Lucia and Siettos, Constantinos I

Reference 62

Resolution
unresolved
no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:30e055ab6a7ebe9ff188e9db6c157beb682392b72066421556b5830f6e3b137e

Observation 1653007d-c21f-4062-a6b6-e9f8eec66ab0 · outbound

This paper cites Physics of Fluids , volume=.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Physics of Fluids , volume=

Reference 63

Resolution
unresolved
no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:f8b9fceeeab563b5a3cf2d8a701be5c61753a74aa7a74a22a46459f0dccd8e0d

Observation 2375e53d-94b9-4288-a9b9-4018d00a497f · outbound

This paper cites Physics of Fluids , volume=.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Physics of Fluids , volume=

Reference 64

Resolution
unresolved
no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:518c690f9630be338770b9cc55818a561df814242114e0699bb75170aad398b3

Observation c46a0f4c-24b6-4167-91ba-c9049ac24330 · outbound

This paper cites and Spruce, Michael and Speares, William , journal=.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws and Spruce, Michael and Speares, William , journal=

Reference 65

Resolution
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no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:08b428043d7f53f0747e6f346b2dfb3c602440705b9888cefdd294e41722edd9

Observation 5091cf04-d697-437a-abc6-793d579f2fbb · outbound

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

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws International Conference on Learning Representations (ICLR) , year=

Reference 66

Resolution
unresolved
no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:79fc1a9ad35313952ac18c2625e4069e49869a2c8e739e5c3c50d109c2362d2c

Observation 3800280e-3e6d-4b83-9f93-84d711292ea4 · outbound

This paper cites International Journal of Computational Fluid Dynamics , volume=.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws International Journal of Computational Fluid Dynamics , volume=

Reference 67

Resolution
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no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:812c00027c85db241158ca134a3fb5510b68c3d35b3ec7bd51cbc4df01b04dcf

Observation b14d9d63-0d3e-4295-aad2-c0b42f9306ab · outbound

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

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws International Conference on Learning Representations (ICLR) , year=

Reference 68

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unresolved
no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:58ad91a625fbe69c5862bd0d899a91640b643a6716c93231412886bd60640985

Observation 6112fd9b-6885-46f9-81c4-0cf97d856a59 · outbound

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

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws International Conference on Learning Representations , year=

Reference 69

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no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:9d23711e04750afcab1adde0e71b60ac6c8b9d9e3c7dbcd102327fce1b2e4ff0

Observation 428ec36a-1615-42e8-b846-2a28ceac121b · outbound

This paper cites Low Reynolds Number Aerodynamics , year =.

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws Low Reynolds Number Aerodynamics , year =

Reference 70

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no resolver link, observed 2026-07-11T19:51:56.544026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:51:56.544026Z digest=sha256:a8f603ef7734b1dfd129d3b8ad6031695d5de82833b1968494179c3d15793519

Pith citing papers

No inbound Pith citation observations are available.