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Paper Citation Record · LEDGER

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction

As of 9 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 9 inbound Pith citation observations for arXiv:2502.04317.

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

pith.paper-citation-record.v1
2502.04317 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T22:55:42.098869Z

measured 28 of 28 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:50:33.788244Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T22:49:10.406943Z

Reference resolution

19 of 19 outbound references displayed

  • verified exact5
  • verified fuzzy3
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e581c969-4771-4b42-9b12-fa0a7f0146d2 · outbound

This paper cites 3.1) e.g.

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction 3.1) e.g

Reference 2

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Source-reported events for the cited work

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Observation 3586930c-965a-47d9-8447-c964deeaadef · outbound

This paper cites Deep Learning for Real-Time Aerodynamic Evaluations of Arbitrary Vehicle Shapes.

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction Deep Learning for Real-Time Aerodynamic Evaluations of Arbitrary Vehicle Shapes

Reference 9

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Observation 93997e33-c521-4c3e-9018-23241e0af2f4 · outbound

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

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction Fourier Neural Operator for Parametric Partial Differential Equations

Reference 13

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Observation a8189013-424f-4111-acbf-8c77e76aa8a9 · outbound

This paper cites Geometry-Informed Neural Operator for Large-Scale 3D PDEs.

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction Geometry-Informed Neural Operator for Large-Scale 3D PDEs

Reference 14

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Observation 9f2429bd-0770-444f-80cf-9a03605cda50 · outbound

This paper cites Jaideep Pathak, Shashank Subramanian, Peter Harrington, Sanjeev Raja, Ashesh Chattopadhyay, Morteza Mardani, Thorsten Kurth, David Hall, Zongyi Li, Kamyar Azizzadenesheli, et al.

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction Jaideep Pathak, Shashank Subramanian, Peter Harrington, Sanjeev Raja, Ashesh Chattopadhyay, Morteza Mardani, Thorsten Kurth, David Hall, Zongyi Li, Kamyar Azizzadenesheli, et al

Reference 15

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Observation 2b4cd92c-1d15-43e0-8873-3a0de7097601 · outbound

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

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction Learning Mesh-Based Simulation with Graph Networks

Reference 16

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Observation 2e18e95b-2b6e-4685-ad98-ab865536c6e6 · outbound

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Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction Unresolved cited work

Reference 18

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Observation bdbb2c05-220b-43a3-816b-ac58f13d5037 · outbound

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Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction Unresolved cited work

Reference 20

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Observation 57fedfea-89a9-400f-9711-49ce9857f3d5 · outbound

This paper cites CP-decomposition with Tensor Power Method for Convolutional Neural Networks Compression.

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction CP-decomposition with Tensor Power Method for Convolutional Neural Networks Compression

Reference 1984

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Observation 2c81a9e1-5e69-4089-8098-55c53cfb6bd3 · outbound

This paper cites Hermosilla, T.

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction Hermosilla, T

Reference 2012

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Observation 03cc343a-316f-4583-ad7b-ce37fd6af147 · outbound

This paper cites Olaf Ronneberger, Philipp Fischer, and Thomas Brox.

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction Olaf Ronneberger, Philipp Fischer, and Thomas Brox

Reference 2013

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Observation 91e60dc2-8508-4151-a731-4247c03d76ff · outbound

This paper cites Kossaifi, A.

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction Kossaifi, A

Reference 2016

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Source-reported events for the cited work

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Observation 997c15d2-82a6-4458-9e7c-2d555e46e3ba · outbound

This paper cites Point Convolutional Neural Networks by Extension Operators.

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction Point Convolutional Neural Networks by Extension Operators

Reference 2017

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Observation 1f1d2059-ada9-4528-a62b-004a27557477 · outbound

This paper cites DrivAerNet: A Parametric Car Dataset for Data-Driven Aerodynamic Design and Prediction.

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction DrivAerNet: A Parametric Car Dataset for Data-Driven Aerodynamic Design and Prediction

Reference 2019

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Observation 5524cd16-51ea-4a59-b3be-c1e86047f88c · outbound

This paper cites doi: 10.1109/CVPR42600.2020.00610.

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction doi: 10.1109/CVPR42600.2020.00610

Reference 2020

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Observation 7ec39723-ed59-466a-bbad-6f3b3a2a064f · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction LoRA: Low-Rank Adaptation of Large Language Models

Reference 2021

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Observation 2418307c-f97f-4048-9c23-1219e959cb03 · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction ShapeNet: An Information-Rich 3D Model Repository

Reference 2022

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Observation 23185571-55aa-4af6-8086-52c4f8ecdec0 · outbound

This paper cites Submanifold Sparse Convolutional Networks.

Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction Submanifold Sparse Convolutional Networks

Reference 2023

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Observation c6dfa21c-1af2-4c9b-b85e-f5fcf45e8fd9 · outbound

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Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction GraphCast: Learning skillful medium-range global weather forecasting

Reference 2024

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Pith citing papers

Observation 8fa91fc0-cc5b-4b42-bd84-b1000391d652 · inbound

Learning Mappings in Mesh-based Simulations cites this paper.

Learning Mappings in Mesh-based Simulations Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction

Reference 15

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A Benchmarking Framework for AI models in Automotive Aerodynamics cites this paper.

A Benchmarking Framework for AI models in Automotive Aerodynamics Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction

Reference 9

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A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics cites this paper.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction

Reference 2

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GeoTransolver: Learning Physics on Irregular Domains Using Multi-scale Geometry Aware Physics Attention Transformer cites this paper.

GeoTransolver: Learning Physics on Irregular Domains Using Multi-scale Geometry Aware Physics Attention Transformer Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction

Reference 32

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Observation 1a7c00ac-974e-4c79-843d-5936acaec1ee · inbound

AeroJEPA: Learning Semantic Latent Representations for Scalable 3D Aerodynamic Field Modeling cites this paper.

AeroJEPA: Learning Semantic Latent Representations for Scalable 3D Aerodynamic Field Modeling Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction

Reference 39

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Observation c70364f2-8c2a-4339-a298-a3b00b358626 · inbound

CarCrashNet: A Large-Scale Dataset and Hierarchical Neural Solver for Data-Driven Structural Crash Simulation cites this paper.

CarCrashNet: A Large-Scale Dataset and Hierarchical Neural Solver for Data-Driven Structural Crash Simulation Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction

Reference 74

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CarCrashNet: A Large-Scale Dataset and Hierarchical Neural Solver for Data-Driven Structural Crash Simulation cites this paper.

CarCrashNet: A Large-Scale Dataset and Hierarchical Neural Solver for Data-Driven Structural Crash Simulation Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction

Reference 61

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Observation 707fed43-d8f9-4e20-80f1-844138be4148 · inbound

ShardTensor: Domain Parallelism for Scientific Machine Learning cites this paper.

ShardTensor: Domain Parallelism for Scientific Machine Learning Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction

Reference 50

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Observation d37daf3b-f724-4922-97b5-b1072280be1c · inbound

HiLiftAeroML: High-Fidelity Computational Fluid Dynamics Dataset for High-Lift Aircraft Aerodynamics cites this paper.

HiLiftAeroML: High-Fidelity Computational Fluid Dynamics Dataset for High-Lift Aircraft Aerodynamics Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction

Reference 10

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