Paper Citation Record · LEDGER

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting

As of 13 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2411.11592.

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

pith.paper-citation-record.v1
2411.11592 v1

Coverage vector

measured 49 of 49 reference resolution

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Reference resolution

49 of 49 outbound references displayed

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External citation measurements

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Outbound references

Observation a31bc885-690d-45df-9502-ac11b6980af3 · outbound

This paper cites an unresolved cited work.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

Reference 1

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Observation 185f6f0d-652d-40ad-8b39-b3d974da5924 · outbound

This paper cites Blazek, Computational fluid dynamics: principles and applications, Butterworth-Heinemann, 2015.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Blazek, Computational fluid dynamics: principles and applications, Butterworth-Heinemann, 2015

Reference 2

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Observation 190f8e05-c004-4c0d-af87-f473a23c9c8f · outbound

This paper cites Sabater, P.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Sabater, P

Reference 3

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Observation adda8bfe-c1d5-4fba-bbcc-a4e2480390aa · outbound

This paper cites Castellanos, J.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Castellanos, J

Reference 4

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Observation b585b8c2-b7a1-4850-bca4-1c68174ba23d · outbound

This paper cites Immordino, A.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Immordino, A

Reference 5

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Observation 033d8fda-3edb-415c-b491-82e623d3a2b7 · outbound

This paper cites Accelerating Eulerian Fluid Simulation With Convolutional Networks.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Accelerating Eulerian Fluid Simulation With Convolutional Networks

Reference 6

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This paper cites an unresolved cited work.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

Reference 7

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This paper cites an unresolved cited work.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

Reference 8

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Observation 5180fcc3-6da2-40fc-9504-acc74b0c66ff · outbound

This paper cites Scarselli, M.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Scarselli, M

Reference 9

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

Reference 10

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Observation 574b1e36-532c-4be6-8ca6-8e5420de36b6 · outbound

This paper cites Zhang, P.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Zhang, P

Reference 11

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This paper cites an unresolved cited work.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

Reference 12

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Observation 0a3d27fc-0e20-4819-912c-ca22d4634239 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Semi-Supervised Classification with Graph Convolutional Networks

Reference 13

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This paper cites an unresolved cited work.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

Reference 14

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Observation 603f6b65-4f9c-4e48-839e-1df9cc7efbc3 · outbound

This paper cites Fukami, K.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Fukami, K

Reference 15

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Observation 8d63c5ce-d9d5-429d-aa2b-f7af4efae232 · outbound

This paper cites Omata, S.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Omata, S

Reference 16

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

Reference 17

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Observation b7707dc8-6787-4751-bf1a-3bc3df95aadb · outbound

This paper cites Rozov, C.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Rozov, C

Reference 18

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

Reference 19

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Observation 63573d29-625b-409a-9964-9aa65bd9ff39 · outbound

This paper cites Saetta, R.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Saetta, R

Reference 20

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Observation dca17d11-3f48-4dfc-aecd-1af5e6102e44 · outbound

This paper cites Massegur Sampietro, A.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Massegur Sampietro, A

Reference 21

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

Reference 22

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Observation f11fdf4d-c2f0-4009-91f9-f1bf84779714 · outbound

This paper cites Vincent, H.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Vincent, H

Reference 23

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Observation 29882bdc-3b6e-46a9-88c4-f896d5e94e92 · outbound

This paper cites Predicting Transonic Flowfields in Non-Homogeneous Unstructured Grids Using Autoencoder Graph Convolutional Networks.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Predicting Transonic Flowfields in Non-Homogeneous Unstructured Grids Using Autoencoder Graph Convolutional Networks

Reference 24

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Observation ea3e1db8-42db-4cbc-8a6b-dae4e536f0c9 · outbound

This paper cites Hochreiter, J.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Hochreiter, J

Reference 25

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Observation 18605c68-dee0-4661-9c0b-c9c9e6199b67 · outbound

This paper cites On the Properties of Neural Machine Translation: Encoder-Decoder Approaches.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting On the Properties of Neural Machine Translation: Encoder-Decoder Approaches

Reference 26

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Observation 6d5389b7-58dc-4e69-93cc-1db2d77938ed · outbound

This paper cites Recent Advances in Recurrent Neural Networks.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Recent Advances in Recurrent Neural Networks

Reference 27

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

Reference 28

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

Reference 29

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

Reference 30

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Observation 55edbd7f-f2ac-4a8c-8c51-79888e31a863 · outbound

This paper cites Mannarino, P.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Mannarino, P

Reference 31

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Observation 038f5fce-a2d9-42d1-956f-90a80ba58015 · outbound

This paper cites Attention Is All You Need.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Attention Is All You Need

Reference 32

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Long Short-Term Memory-Networks for Machine Reading

Reference 33

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Observation f62ab3ef-ddba-483f-bbc3-727408e8d1a4 · outbound

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Cheng, F

Reference 34

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Predicting Physics in Mesh-reduced Space with Temporal Attention

Reference 35

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

Reference 36

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Observation dad3e9c9-4d13-4146-be81-a2f55507700e · outbound

This paper cites A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting A3T-GCN: Attention Temporal Graph Convolutional Network for Traffic Forecasting

Reference 37

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Observation 782e17b6-e7c2-4e3b-a1bb-f1ffe4b7c64e · outbound

This paper cites Convolutional Networks on Graphs for Learning Molecular Fingerprints.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Convolutional Networks on Graphs for Learning Molecular Fingerprints

Reference 38

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This paper cites Fast Graph Representation Learning with PyTorch Geometric.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Fast Graph Representation Learning with PyTorch Geometric

Reference 39

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

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This paper cites Structured Sequence Modeling with Graph Convolutional Recurrent Networks.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Structured Sequence Modeling with Graph Convolutional Recurrent Networks

Reference 42

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting

Reference 43

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting De Maesschalck, D

Reference 44

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This paper cites Heeg, Overview of the aeroelastic prediction workshop, in: 51st AIAA aerospace sciences meeting including the new horizons forum and aerospace exposition, 2013, p.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Heeg, Overview of the aeroelastic prediction workshop, in: 51st AIAA aerospace sciences meeting including the new horizons forum and aerospace exposition, 2013, p

Reference 45

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

Reference 46

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Adam: A Method for Stochastic Optimization

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Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Unresolved cited work

Reference 654

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This paper cites Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting.

Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting

Reference 2015

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Pith citing papers

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