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Paper Citation Record · LEDGER

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics

As of 7 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 1 inbound Pith citation observation for arXiv:2508.21249.

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

pith.paper-citation-record.v1
2508.21249 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:29:31.176289Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T12:39:34.792801Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T11:46:18.980347Z

Reference resolution

21 of 21 outbound references displayed

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External citation measurements

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Outbound references

Observation 4535a9e4-cadf-4c0b-99db-eaecbaf88642 · outbound

This paper cites DrivAerML: High-Fidelity Computational Fluid Dynamics Dataset for Road-Car External Aerodynamics.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics DrivAerML: High-Fidelity Computational Fluid Dynamics Dataset for Road-Car External Aerodynamics

Reference 1

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Observation 52efafe4-79b0-490c-89bf-50e03300239b · outbound

This paper cites Factorized Implicit Global Convolution for Automotive Computational Fluid Dynamics Prediction.

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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Observation 1a177505-e9b0-4bc8-b3d5-d823ddfe0f07 · outbound

This paper cites Machine learning–accelerated computational fluid dynamics.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics Machine learning–accelerated computational fluid dynamics

Reference 3

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Observation 216def5d-4312-44b1-a944-96355e13a63f · outbound

This paper cites Machine learning for road vehicle aerodynamics.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics Machine learning for road vehicle aerodynamics

Reference 4

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Observation fab9d7fa-fd75-4772-8459-f8f47324eb22 · outbound

This paper cites Neural Con- cept, accessed August 27, 2025, https://www.neuralconcept.com/post/ applying-machine-learning-in-cfd-to-accelerate-simulation.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics Neural Con- cept, accessed August 27, 2025, https://www.neuralconcept.com/post/ applying-machine-learning-in-cfd-to-accelerate-simulation

Reference 5

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Observation be4dc481-5ea8-42b5-b2c4-0fe175aa1335 · outbound

This paper cites Neuralcfd: Deep learning on high-fidelity automotive aerodynamics simulations.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics Neuralcfd: Deep learning on high-fidelity automotive aerodynamics simulations

Reference 6

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Observation f1174164-324d-416a-b578-fa5376ca6a32 · outbound

This paper cites Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 7

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Observation 0c6ee588-2149-46c3-8d6b-2261a09925a9 · outbound

This paper cites NVIDIA Docs, accessed August 27, 2025, https://docs.nvidia.com/deeplearning/physicsnemo/physicsnemo-core/examples/ cfd/vortex_shedding_mgn/readme.html.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics NVIDIA Docs, accessed August 27, 2025, https://docs.nvidia.com/deeplearning/physicsnemo/physicsnemo-core/examples/ cfd/vortex_shedding_mgn/readme.html

Reference 8

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Observation c913a851-1058-49ae-a958-0b43eb257bfc · outbound

This paper cites Reducing frequency bias of fourier neural operators in 3d seismic wavefield simulations through multistage training.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics Reducing frequency bias of fourier neural operators in 3d seismic wavefield simulations through multistage training

Reference 9

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Observation 64ab2f5e-f560-4d6b-9db8-67d63a598226 · outbound

This paper cites Efficient learning of mesh-based physical simulation with bi-stride multi-scale graph neural network.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics Efficient learning of mesh-based physical simulation with bi-stride multi-scale graph neural network

Reference 10

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Observation a1bf9560-cc14-465e-9299-36d3fc9b03c6 · outbound

This paper cites Hierarchical mixtures of experts and the em algorithm.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics Hierarchical mixtures of experts and the em algorithm

Reference 11

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Observation c230685d-4c23-43b4-94ad-ca6f30810371 · outbound

This paper cites DataCamp, accessed August 27, 2025, https://www.datacamp.com/blog/mixture-of-experts-moe.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics DataCamp, accessed August 27, 2025, https://www.datacamp.com/blog/mixture-of-experts-moe

Reference 12

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Observation d7a07f8c-b011-4e16-a79b-47ba18de0cfd · outbound

This paper cites ˇCVUT DSpace, accessed August 27, 2025, https://dspace.cvut.cz/bitstream/handle/ 10467/123538/F3-BP-2025-Bakhtigariev-Robert-thesis.pdf.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics ˇCVUT DSpace, accessed August 27, 2025, https://dspace.cvut.cz/bitstream/handle/ 10467/123538/F3-BP-2025-Bakhtigariev-Robert-thesis.pdf

Reference 13

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Observation 6a21982e-583b-432d-b3b0-d0e09507788b · outbound

This paper cites DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations

Reference 14

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This paper cites Deus Ex Machina, ac- cessed August 27, 2025, https://deus-ex-machina-ism.com/?p=68105&lang=en.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics Deus Ex Machina, ac- cessed August 27, 2025, https://deus-ex-machina-ism.com/?p=68105&lang=en

Reference 15

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Observation a1f6fbbb-a543-4033-9475-077299976887 · outbound

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

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics X-MeshGraphNet: Scalable Multi-Scale Graph Neural Networks for Physics Simulation

Reference 16

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Observation b82a6c1a-b2c4-4ba2-b39d-d8d5232fffb2 · outbound

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A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics MultiScale MeshGraphNets

Reference 17

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Observation 96801e3e-fbad-4856-bf5f-710786d5ddd2 · outbound

This paper cites Integrated surrogate model-based approach for aerodynamic design optimization of three-stage axial compressor in gas turbine applications.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics Integrated surrogate model-based approach for aerodynamic design optimization of three-stage axial compressor in gas turbine applications

Reference 18

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Observation aecf14ab-00ed-4e0a-8ef1-8519f28f00a1 · outbound

This paper cites The application of ensemble machine learning methods for construction of surrogate models in problems of preliminary design of an aircraft wing airfoil.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics The application of ensemble machine learning methods for construction of surrogate models in problems of preliminary design of an aircraft wing airfoil

Reference 19

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Observation 5295b756-0273-4ffd-8f04-1f7a2b2747f0 · outbound

This paper cites Airfoil aerodynamic optimization design using ensemble learning surrogate model.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics Airfoil aerodynamic optimization design using ensemble learning surrogate model

Reference 20

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Observation 4a2be4ee-44f8-4b54-9c0d-9b6ec81dd3da · outbound

This paper cites A comprehensive survey of mixture-of-experts: Algorithms, theory, and applications.

A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics A comprehensive survey of mixture-of-experts: Algorithms, theory, and applications

Reference 21

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Pith citing papers

Observation dc26af43-e5ec-4cc2-8249-0036cb51d98b · inbound

AeTHERON: Autoregressive Topology-aware Heterogeneous Graph Operator Network for Fluid-Structure Interaction cites this paper.

AeTHERON: Autoregressive Topology-aware Heterogeneous Graph Operator Network for Fluid-Structure Interaction A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics

Reference 8

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