Paper Citation Record · LEDGER

Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2409.08477.

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

pith.paper-citation-record.v1
2409.08477 v2

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measured 0 of 0 reference resolution

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measured 25 of 25 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:16:23.065563Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T08:57:47.596952Z

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Outbound references

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Pith citing papers

Observation 704cfe7e-6a94-4f14-b2f0-d1dd0408018e · inbound

Implicit factorized transformer approach to fast prediction of turbulent channel flows cites this paper.

Implicit factorized transformer approach to fast prediction of turbulent channel flows Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 33

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Observation b1dd858b-990f-475c-9c5e-7bbff280e302 · inbound

MscaleFNO: Multi-scale Fourier Neural Operator Learning for Oscillatory Function Spaces cites this paper.

MscaleFNO: Multi-scale Fourier Neural Operator Learning for Oscillatory Function Spaces Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T23:32:57.350901Z

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Observation 4396cb77-8369-4737-a500-c03fd6f87324 · inbound

DeepVIVONet: Using deep neural operators to optimize sensor locations with application to vortex-induced vibrations cites this paper.

DeepVIVONet: Using deep neural operators to optimize sensor locations with application to vortex-induced vibrations Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 22

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Observation 10759cce-c25c-4fd1-9809-cd396fc8279a · inbound

On understanding and overcoming spectral biases of deep neural network learning methods for solving PDEs cites this paper.

On understanding and overcoming spectral biases of deep neural network learning methods for solving PDEs Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 129

Resolution: unresolved; no resolver link, observed 2026-08-10T19:32:41.836234Z

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Observation 4cc8d3f2-4a95-4d2d-bb77-f32de2fca7e2 · inbound

Equilibrium Conserving Neural Operators for Super-Resolution Learning cites this paper.

Equilibrium Conserving Neural Operators for Super-Resolution Learning Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-16T12:16:23.065563Z

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Observation 09cab297-75ed-47e4-b86b-3e8893cd400c · inbound

Physics-based super-resolved simulation of 3D elastic wave propagation adopting scalable Diffusion Transformer cites this paper.

Physics-based super-resolved simulation of 3D elastic wave propagation adopting scalable Diffusion Transformer Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-16T10:48:14.364351Z

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Observation 6034d696-d0c9-4d13-a01c-002a12d888dd · inbound

Monotone Peridynamic Neural Operator for Nonlinear Material Modeling with Conditionally Unique Solutions cites this paper.

Monotone Peridynamic Neural Operator for Nonlinear Material Modeling with Conditionally Unique Solutions Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-16T04:36:41.003370Z

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Observation 91edc3c5-4bba-4570-83dd-37785681a97b · inbound

FLEX: A Backbone for Diffusion-Based Modeling of Spatio-temporal Physical Systems cites this paper.

FLEX: A Backbone for Diffusion-Based Modeling of Spatio-temporal Physical Systems Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T14:55:04.504837Z

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Observation e13a31ff-8ba3-4be7-8ca5-ab2b2b5f2677 · inbound

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

FourierFlow: Frequency-aware Flow Matching for Generative Turbulence Modeling Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:18.563580Z

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Observation 38844e9c-a9e0-409d-9aa3-57912302ee27 · inbound

PolyMicros: Bootstrapping a Foundation Model for Polycrystalline Material Structure cites this paper.

PolyMicros: Bootstrapping a Foundation Model for Polycrystalline Material Structure Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:19.346952Z

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Observation 0da82717-4d9f-4160-ac2a-7a8c4f6d8e98 · inbound

Bridging Sequential Deep Operator Network and Video Diffusion: Residual Refinement of Spatio-Temporal PDE Solutions cites this paper.

Bridging Sequential Deep Operator Network and Video Diffusion: Residual Refinement of Spatio-Temporal PDE Solutions Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T19:16:30.864772Z

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Observation 5574d4a7-f51d-4d00-80a6-2ed86394303a · inbound

Generative Lagrangian data assimilation for ocean dynamics under extreme sparsity cites this paper.

Generative Lagrangian data assimilation for ocean dynamics under extreme sparsity Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T19:08:48.599402Z

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Observation 0f6068cd-ff9a-4d3e-96b7-da12b4eb8c85 · inbound

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting cites this paper.

DETNO: A Diffusion-Enhanced Transformer Neural Operator for Long-Term Traffic Forecasting Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T15:53:00.174651Z

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Observation 52179522-052a-4cc6-b76f-d229dd364c0a · inbound

Flow marching for a generative PDE foundation model cites this paper.

Flow marching for a generative PDE foundation model Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:51:25.621333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fe636cc9-cce7-49d5-aa5b-fb1b87c08574 · inbound

Softly Constrained Denoisers for Diffusion Models Applied to Partial Differential Equations cites this paper.

Softly Constrained Denoisers for Diffusion Models Applied to Partial Differential Equations Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-03T15:59:12.336001Z

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Observation f696f109-2c4d-4c56-8840-486ec2c6044d · inbound

Physics-informed diffusion models in spectral space cites this paper.

Physics-informed diffusion models in spectral space Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T02:51:57.665522Z

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Observation e6807bd1-1a70-4058-86b8-3c59db44c1c1 · inbound

Latent Generative Solvers for Generalizable Long-Term Physics Simulation cites this paper.

Latent Generative Solvers for Generalizable Long-Term Physics Simulation Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T05:22:22.686647Z

Source-reported events for the cited work

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Observation 82b9d596-f65b-4a00-bb5c-f79d805b1c92 · inbound

MENO: MeanFlow-Enhanced Neural Operators for Dynamical Systems cites this paper.

MENO: MeanFlow-Enhanced Neural Operators for Dynamical Systems Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:20:51.447512Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8696be08-1716-498a-90a0-a50feb654e10 · inbound

MENO: MeanFlow-Enhanced Neural Operators for Dynamical Systems cites this paper.

MENO: MeanFlow-Enhanced Neural Operators for Dynamical Systems Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-13T08:47:34.631129Z

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Observation d118004b-678f-4e33-a655-27f9ccff7eac · inbound

Predictivity and Utility of Neural Surrogates of Multiscale PDEs cites this paper.

Predictivity and Utility of Neural Surrogates of Multiscale PDEs Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:46:03.747193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation d6056a9a-6aed-4cf3-a60e-2bace6763a78 · inbound

Autoregressive One-Step Generative Modeling for Dynamical System Forecasting cites this paper.

Autoregressive One-Step Generative Modeling for Dynamical System Forecasting Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T14:48:33.337690Z

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Observation bf5a6d9c-d948-4148-acc8-b192c85a37f9 · inbound

Wavelet Flow Matching for Multi-Scale Physics Emulation cites this paper.

Wavelet Flow Matching for Multi-Scale Physics Emulation Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-20T19:33:41.871290Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation ead6c02c-6146-4cb2-bd64-85d3f33e735e · inbound

Correcting Neural Operator Spectral Bias via Diffusion Posterior Sampling with Sparse Observations cites this paper.

Correcting Neural Operator Spectral Bias via Diffusion Posterior Sampling with Sparse Observations Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-02T02:06:27.728784Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 32fdb337-f198-4914-bb13-4670b8c74e06 · inbound

Multiscale Fourier Neural Operator for Inverse Wave Scattering in Highly Oscillatory Media cites this paper.

Multiscale Fourier Neural Operator for Inverse Wave Scattering in Highly Oscillatory Media Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 36

Resolution: malformed identifier; arxiv_id, observed 2026-07-02T23:27:27.404472Z

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation e533a73e-5c45-4815-856f-0250793fece2 · inbound

Spectrally Regularized Latent Flow Matching for Turbulence Generation cites this paper.

Spectrally Regularized Latent Flow Matching for Turbulence Generation Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-07-03T08:57:47.598465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.