Paper Citation Record · LEDGER

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries

As of 21 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2607.11672.

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

pith.paper-citation-record.v1
2607.11672 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T03:58:20.710039Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

24 of 24 outbound references displayed

verified exact0
verified fuzzy0
unresolved24
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f0b32e2c-9d34-4463-820c-f59d55e2f4e8 · outbound

This paper cites Relational inductive biases, deep learning, and graph networks.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Relational inductive biases, deep learning, and graph networks

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c563e95-9ff8-4617-95fb-c1cc59ea96d0 · outbound

This paper cites AirfRANS: High fidelity compu- tational fluid dynamics dataset for approximating reynolds-averaged navier–stokes solutions, in: NeurIPS Datasets and Benchmarks Track.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries AirfRANS: High fidelity compu- tational fluid dynamics dataset for approximating reynolds-averaged navier–stokes solutions, in: NeurIPS Datasets and Benchmarks Track

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bb75416-5f4a-4860-9a00-35768e6c5fbb · outbound

This paper cites Choose a transformer: Fourier or galerkin, in: NeurIPS.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Choose a transformer: Fourier or galerkin, in: NeurIPS

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ee46b9f-76a8-4253-8673-271cbffd27d0 · outbound

This paper cites Geometry-guided conditional adaption for surrogate models of large-scale 3d PDEs on arbitrary geometries, in: IJCAI.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Geometry-guided conditional adaption for surrogate models of large-scale 3d PDEs on arbitrary geometries, in: IJCAI

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e5e5191-b503-464b-a032-0db9503292b0 · outbound

This paper cites Drivaernet: A parametric car dataset for data-driven aerodynamic design and graph-based drag prediction.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Drivaernet: A parametric car dataset for data-driven aerodynamic design and graph-based drag prediction

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 453b57a9-8cf2-49c5-90ff-eae7fca51713 · outbound

This paper cites PhyGeoNet: Physics-informed geometry-adaptive convolu- tional neural networks for solving parameterized steady-state PDEs on irregular domain.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries PhyGeoNet: Physics-informed geometry-adaptive convolu- tional neural networks for solving parameterized steady-state PDEs on irregular domain

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71c6d810-98c6-42cd-9022-f426c7998b78 · outbound

This paper cites Gnot: A general neural operator transformer for operator learning, in: International Conference on Ma- chine Learning, PMLR.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Gnot: A general neural operator transformer for operator learning, in: International Conference on Ma- chine Learning, PMLR

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b7fe8ef-d57c-4bbe-bb75-023670baa99b · outbound

This paper cites Brain Tumor Segmentation and Survival Prediction using 3D Attention UNet.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Brain Tumor Segmentation and Survival Prediction using 3D Attention UNet

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 631fd65a-11ad-4cae-8a80-2326f8526c2f · outbound

This paper cites Predicting unsteady incompressible fluid dynamics with finite volume informed neural network.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Predicting unsteady incompressible fluid dynamics with finite volume informed neural network

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25139f4a-8b90-4928-92e3-dd5798265098 · outbound

This paper cites A fully differentiable GNN-based PDE Solver: With Applications to Poisson and Navier-Stokes Equations.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries A fully differentiable GNN-based PDE Solver: With Applications to Poisson and Navier-Stokes Equations

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fc2e534-0e92-409f-a380-0b0153e63655 · outbound

This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Fourier Neural Operator for Parametric Partial Differential Equations

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dea499be-bf77-4f6c-8341-48d9d577f8f4 · outbound

This paper cites Neural Operator: Graph Kernel Network for Partial Differential Equations.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Neural Operator: Graph Kernel Network for Partial Differential Equations

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffd416ad-a92b-4178-bc1c-99bd8202699d · outbound

This paper cites Geometry-informed neural operator for large- scale 3d PDEs, in: NeurIPS.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Geometry-informed neural operator for large- scale 3d PDEs, in: NeurIPS

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7eff554-f5a4-4f50-9c51-808a2d46cf57 · outbound

This paper cites Learning nonlinear operators via deeponet based on the universal approximation theorem of operators.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Learning nonlinear operators via deeponet based on the universal approximation theorem of operators

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c4501f1-24e9-4ce0-a9b2-9723a48d58e6 · outbound

This paper cites Geometric deep learning on graphs and manifolds using mixture model cnns, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Geometric deep learning on graphs and manifolds using mixture model cnns, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b5172f9-82e9-4ed5-9f3d-09ae97e944e4 · outbound

This paper cites K-hop graph neural networks.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries K-hop graph neural networks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38b24019-f625-4494-b581-6c1df21868aa · outbound

This paper cites FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb553324-9364-438d-926b-940889fffb08 · outbound

This paper cites Learning Mesh-Based Simulation with Graph Networks.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Learning Mesh-Based Simulation with Graph Networks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 347c37e1-2505-47e6-a01b-5ffa3c301afd · outbound

This paper cites Learn- ing to simulate complex physics with graph networks, in: International Conference on Machine Learning, PMLR.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Learn- ing to simulate complex physics with graph networks, in: International Conference on Machine Learning, PMLR

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8dede040-80c7-42fa-a4e8-4fbf9a879cd2 · outbound

This paper cites Graph networks as learnable physics engines for inference and control, in: International Conference on Machine Learning, PMLR.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Graph networks as learnable physics engines for inference and control, in: International Conference on Machine Learning, PMLR

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d0d7d56-b97a-434b-9834-0d11c19f1e77 · outbound

This paper cites Aerodynamics- guided machine learning for design optimization of electric vehicles.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Aerodynamics- guided machine learning for design optimization of electric vehicles

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c2f52d9-b712-4767-964e-e183f9619265 · outbound

This paper cites Learning three-dimensional flow for interactive aerodynamic de- sign.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Learning three-dimensional flow for interactive aerodynamic de- sign

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4f9bcb1-716d-4bbb-a3e2-5c9369fdb235 · outbound

This paper cites Transolver: A Fast Transformer Solver for PDEs on General Geometries.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Transolver: A Fast Transformer Solver for PDEs on General Geometries

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aaba1db0-1a12-4830-8b69-c9dd5a31b278 · outbound

This paper cites Graph neural networks: A review of methods and applications.

A multi-scale feature enhanced graph neural network for fluid dynamics prediction in complex geometries Graph neural networks: A review of methods and applications

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-14T03:58:20.710039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.