mlsanityData to 7 Oct 2026

DiffFluid: Plain Diffusion Models are Effective Predictors of Flow Dynamics

arXiv 2409.13665 ↗First posted 20 Sep 2024cs.LG physics.flu-dyncited by 4

On the map: Diffusion models → Flow matching, time series and science

Abstract (arXiv)

We showcase the plain diffusion models with Transformers are effective predictors of fluid dynamics under various working conditions, e.g., Darcy flow and high Reynolds number. Unlike traditional fluid dynamical solvers that depend on complex architectures to extract intricate correlations and learn underlying physical states, our approach formulates the prediction of flow dynamics as the image translation problem and accordingly leverage the plain diffusion model to tackle the problem. This reduction in model design complexity does not compromise its ability to capture complex physical states and geometric features of fluid dynamical equations, leading to high-precision solutions. In preliminary tests on various fluid-related benchmarks, our DiffFluid achieves consistent state-of-the-art performance, particularly in solving the Navier-Stokes equations in fluid dynamics, with a relative precision improvement of +44.8%. In addition, we achieved relative improvements of +14.0% and +11.3% in the Darcy flow equation and the airfoil problem with Euler's equation, respectively. Code will be released at https://github.com/DongyuLUO/DiffFluid upon acceptance.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Placed in Flow matching, time series and science, one of 14 directions in Diffusion models. Builds on 37 of its 51 references that are in the map. First posted on arXiv 20 Sep 2024.

Builds on

37 of 51 references.

References · 37

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  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  3. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
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25 more
  1. 2020Reformer: The Efficient Transformercited by 1,658
  2. 2020Rethinking Attention with Performerscited by 1,584
  3. 2021Cascaded Diffusion Models for High Fidelity Image Generationcited by 1,155
  4. 2020Neural Operator: Graph Kernel Network for Partial Differential Equationscited by 722
  5. 2023Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generatorscited by 666
  6. 2023AudioLDM: Text-to-Audio Generation with Latent Diffusion Modelscited by 592
  7. 2022Fourier Neural Operator with Learned Deformations for PDEs on General Geometriescited by 416
  8. 2021SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Modelscited by 415
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  15. 2022Transformer for Partial Differential Equations' Operator Learningcited by 270
  16. 2023DiffIR: Efficient Diffusion Model for Image Restorationcited by 253
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  18. 2021Multiwavelet-based Operator Learning for Differential Equationscited by 229
  19. 2021Gradient-enhanced physics-informed neural networks for forward and inverse PDE problemscited by 220
  20. 2022U-NO: U-shaped Neural Operatorscited by 219
  21. 2023Scalable Transformer for PDE Surrogate Modelingcited by 123
  22. 2021PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEscited by 97
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 3; 2026: 1.

4 papers.

  1. 2025FLEX: A Backbone for Diffusion-Based Modeling of Spatio-temporal Physical Systemscited by 8
  2. 2025Efficient probabilistic surrogate modeling techniques for partially-observed large-scale dynamical systemscited by 1
  3. 2026HPG-Diff: Hierarchical physics-guided diffusion with differentiable connectivity constraints for topology optimizationcited by 1
  4. 2025Predicting Flow Dynamics using Diffusion Modelscited by 0

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  1. 2023A Denoising Diffusion Model for Fluid Field Prediction
  2. 2025Autoregressive regularized score-based diffusion models for multi-scenarios fluid flow prediction
  3. 2026Fluid-DiT: Graph-Free Diffusion Transformers for Fluid Flow Simulations Learning
  4. 2025Guiding diffusion models to reconstruct flow fields from sparse data
  5. 2023Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation
  6. 2024Leveraging Previous Steps: A Training-free Fast Solver for Flow Diffusion
  7. 2026Coupled Diffusion-Encoder Models for Reconstruction of Flow Fields
  8. 2024PiRD: Physics-informed Residual Diffusion for Flow Field Reconstruction