Paper Citation Record · LEDGER

Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 23 inbound Pith citation observations for arXiv:2408.12171.

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

pith.paper-citation-record.v1
2408.12171 v1

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 23 of 23 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 23 of 23 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:02:12.842848Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

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External citation measurements

29
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 352168f0-7f1c-4eb8-9672-adc5cc91208d · inbound

PINS: Proximal Iterations with Sparse Newton and Sinkhorn for Optimal Transport cites this paper.

PINS: Proximal Iterations with Sparse Newton and Sinkhorn for Optimal Transport Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-23T03:27:27.178941Z

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.

Observation d1567126-367a-45fc-b320-60ae09b8d5a8 · inbound

A Multimodal PDE Foundation Model for Prediction and Scientific Text Descriptions cites this paper.

A Multimodal PDE Foundation Model for Prediction and Scientific Text Descriptions Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-08T17:02:12.842848Z

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Observation d8bf9b9d-a277-47d3-b566-ba6faa0a5a0d · inbound

Hierarchical-embedding autoencoder with a predictor (HEAP) as efficient architecture for learning long-term evolution of complex multi-scale physical systems cites this paper.

Hierarchical-embedding autoencoder with a predictor (HEAP) as efficient architecture for learning long-term evolution of complex multi-scale physical systems Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:44.143380Z

Source-reported events for the cited work

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Observation 8dd734e5-44e5-4b60-9ef3-84e47b5d1d03 · inbound

FD-Bench: A Modular and Fair Benchmark for Data-driven Fluid Simulation cites this paper.

FD-Bench: A Modular and Fair Benchmark for Data-driven Fluid Simulation Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 107

Resolution: verified exact; arxiv_id, observed 2026-05-22T13:01:33.954254Z

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.

Observation d98c6009-0fa1-44a8-b6c2-e9c118578c6c · inbound

Spectral-inspired Operator Learning with Limited Data and Unknown Physics cites this paper.

Spectral-inspired Operator Learning with Limited Data and Unknown Physics Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-25T08:30:31.472817Z

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.

Observation 48910c22-ae8c-4d13-bc6b-487ded12fe1c · inbound

FourierFlow: Frequency-aware Flow Matching for Generative Turbulence Modeling cites this paper.

FourierFlow: Frequency-aware Flow Matching for Generative Turbulence Modeling Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:18.647758Z

Source-reported events for the cited work

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Observation ef5cfd66-5220-4cb3-8e5b-cef1d2f2397d · inbound

Diffeomorphic Neural Operator Learning cites this paper.

Diffeomorphic Neural Operator Learning Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-05T22:39:54.621700Z

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Observation 1ebdd592-b47d-4525-8ac7-8b3a8f815649 · inbound

Data-driven optimized high-order WENO schemes with low-dissipation and low-dispersion cites this paper.

Data-driven optimized high-order WENO schemes with low-dissipation and low-dispersion Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-05T20:07:31.575820Z

Source-reported events for the cited work

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

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 Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T14:29:29.515527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1fa41c9-7aff-42fa-b658-45790a1ed3a5 · inbound

Multi-Stage Graph Neural Networks for Data-Driven Prediction of Natural Convection in Enclosed Cavities cites this paper.

Multi-Stage Graph Neural Networks for Data-Driven Prediction of Natural Convection in Enclosed Cavities Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-05T04:38:44.282207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1df73cd0-1cd9-438d-ad12-cc2761c3ade5 · inbound

M4GN: Mesh-based Multi-segment Hierarchical Graph Network for Dynamic Simulations cites this paper.

M4GN: Mesh-based Multi-segment Hierarchical Graph Network for Dynamic Simulations Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T17:48:35.939705Z

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Observation 11dd1ce4-a1ca-497d-ab25-ac8ebabcccdd · inbound

Incomplete Data, Complete Dynamics: A Diffusion Approach cites this paper.

Incomplete Data, Complete Dynamics: A Diffusion Approach Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-18T14:21:28.319110Z

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.

Observation 92809621-65ea-4d5c-82aa-1b69dc025eb2 · inbound

A review of quantum machine learning and quantum-inspired applied methods to computational fluid dynamics cites this paper.

A review of quantum machine learning and quantum-inspired applied methods to computational fluid dynamics Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-18T06:42:26.485701Z

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.

Observation 8314ee86-cb8c-49da-9139-58f1c6a43828 · inbound

Encoding strategies for quantum enhanced fluid simulations: opportunities and challenges cites this paper.

Encoding strategies for quantum enhanced fluid simulations: opportunities and challenges Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:56:11.365780Z

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.

Observation 177ed8c8-a4b2-419f-b3b4-0a2b28f8587f · inbound

DeepPropNet: an operator learning-based predictor for thermal plasma properties cites this paper.

DeepPropNet: an operator learning-based predictor for thermal plasma properties Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:51:28.078703Z

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.

Observation 6a22dec2-b7c0-42b1-80a4-1477a117065f · inbound

Deep Wave Network for Modeling Multi-Scale Physical Dynamics cites this paper.

Deep Wave Network for Modeling Multi-Scale Physical Dynamics Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:31:04.700131Z

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.

Observation b7bd19a0-f0c4-4fe7-a5ad-4551cb6676ee · inbound

PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting cites this paper.

PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 147

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:21:25.921637Z

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.

Observation 968bc62f-5257-465c-959d-a6b129781d13 · inbound

PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting cites this paper.

PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 147

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:22:59.085280Z

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.

Observation c811e562-5657-4d6e-a761-0535d17c285b · inbound

Harnessing AI for Inverse Partial Differential Equation Problems: Past, Present, and Prospects cites this paper.

Harnessing AI for Inverse Partial Differential Equation Problems: Past, Present, and Prospects Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 223

Resolution: verified exact; arxiv_id, observed 2026-05-19T20:32:45.662236Z

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.

Observation 1b35330d-13d8-4065-8b74-0190ba578467 · inbound

Is Zero-Shot Super-Resolution Possible in Operator Learning? cites this paper.

Is Zero-Shot Super-Resolution Possible in Operator Learning? Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 103

Resolution: verified exact; arxiv_id, observed 2026-06-28T19:52:34.998223Z

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.

Observation fb920536-75ad-47f8-badc-5c8ac7713e59 · inbound

Solution of the Newtonian plane Couette flow with dynamic wall slip using machine-learning methods cites this paper.

Solution of the Newtonian plane Couette flow with dynamic wall slip using machine-learning methods Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-06-26T22:20:10.190766Z

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.

Observation faba2f5a-cda6-4524-926d-73b1704485ea · inbound

A Physics-Informed Fourier-Wavelet Transformer for Multiscale Computational Fluid Dynamics Surrogate Modeling cites this paper.

A Physics-Informed Fourier-Wavelet Transformer for Multiscale Computational Fluid Dynamics Surrogate Modeling Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-04T18:30:02.730661Z

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.

Observation f8486cf9-8d89-42d5-8c98-e4789cf482b4 · inbound

Hybrid Lagrangian-Eulerian Model for Lagrangian Fluid Simulation cites this paper.

Hybrid Lagrangian-Eulerian Model for Lagrangian Fluid Simulation Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-06T00:30:47.397745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.