SIMR-NO: A Spectrally-Informed Multi-Resolution Neural Operator for Turbulent Flow Super-Resolution
Fuente:
arXiv
Saved in:
| Main Authors: | Abid, Muhammad, San, Omer |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
The impact of observation density on Bayesian inversion of latent dynamics in shock-dominated flows
by: Tiwari, Bipin, et al.
Published: (2026)
by: Tiwari, Bipin, et al.
Published: (2026)
Implicit Augmentation from Distributional Symmetry in Turbulence Super-Resolution
by: Balla, Julia, et al.
Published: (2025)
by: Balla, Julia, et al.
Published: (2025)
Shape Invariant 3D-Variational Autoencoder: Super Resolution in Turbulence flow
by: Maurya, Anuraj
Published: (2025)
by: Maurya, Anuraj
Published: (2025)
Spectrally Informed Learning of Fluid Flows
by: Shaffer, Benjamin D., et al.
Published: (2024)
by: Shaffer, Benjamin D., et al.
Published: (2024)
Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling
by: Oommen, Vivek, et al.
Published: (2024)
by: Oommen, Vivek, et al.
Published: (2024)
Solving Turbulent Rayleigh-Bénard Convection using Fourier Neural Operators
by: Straat, Michiel, et al.
Published: (2025)
by: Straat, Michiel, et al.
Published: (2025)
Accelerating Bayesian inverse design in computational fluid dynamics using neural operators
by: Tiwari, Bipin, et al.
Published: (2026)
by: Tiwari, Bipin, et al.
Published: (2026)
Guided Unconditional and Conditional Generative Models for Super-Resolution and Inference of Quasi-Geostrophic Turbulence
by: Babu, Anantha Narayanan Suresh, et al.
Published: (2025)
by: Babu, Anantha Narayanan Suresh, et al.
Published: (2025)
Learning Turbulent Flows with Generative Models: Super-resolution, Forecasting, and Sparse Flow Reconstruction
by: Oommen, Vivek, et al.
Published: (2025)
by: Oommen, Vivek, et al.
Published: (2025)
Physics-Informed Graph Neural Network Surrogates for Turbulent Nanoparticle Dispersion in Dental Clinical Environments
by: Shende, Takshak, et al.
Published: (2026)
by: Shende, Takshak, et al.
Published: (2026)
Generative Super-Resolution of Turbulent Flows via Stochastic Interpolants
by: Schiødt, Martin, et al.
Published: (2025)
by: Schiødt, Martin, et al.
Published: (2025)
Mesh-based Super-Resolution of Fluid Flows with Multiscale Graph Neural Networks
by: Barwey, Shivam, et al.
Published: (2024)
by: Barwey, Shivam, et al.
Published: (2024)
Prospects of federated machine learning in fluid dynamics
by: San, Omer, et al.
Published: (2022)
by: San, Omer, et al.
Published: (2022)
Physics-enhanced Neural Operator for Simulating Turbulent Transport
by: Chen, Shengyu, et al.
Published: (2024)
by: Chen, Shengyu, et al.
Published: (2024)
A Physics-Informed Spatiotemporal Deep Learning Framework for Turbulent Systems
by: Menicali, Luca, et al.
Published: (2025)
by: Menicali, Luca, et al.
Published: (2025)
MENO: MeanFlow-Enhanced Neural Operators for Dynamical Systems
by: Yang, Tianyue, et al.
Published: (2026)
by: Yang, Tianyue, et al.
Published: (2026)
Project and Generate: Divergence-Free Neural Operators for Incompressible Flows
by: Li, Xigui, et al.
Published: (2026)
by: Li, Xigui, et al.
Published: (2026)
Multi-scale Dynamic Wake Modeling and Prediction of Floating Offshore Wind Turbines via Physics-Informed Neural Networks and Fourier Neural Operators
by: Dong, Guodan, et al.
Published: (2026)
by: Dong, Guodan, et al.
Published: (2026)
FlowRefiner: Flow Matching-Based Iterative Refinement for 3D Turbulent Flow Simulation
by: Dai, Yilong, et al.
Published: (2026)
by: Dai, Yilong, et al.
Published: (2026)
Superresolving Non-linear PDE Dynamics with Reduced-Order Autodifferentiable Ensemble Kalman Filtering For Turbulence Modeling and Flow Regulation
by: Dhingra, Mrigank, et al.
Published: (2025)
by: Dhingra, Mrigank, et al.
Published: (2025)
Physics-Informed Chebyshev Polynomial Neural Operator for Parametric Partial Differential Equations
by: Chen, Biao, et al.
Published: (2026)
by: Chen, Biao, et al.
Published: (2026)
Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation
by: Kohl, Georg, et al.
Published: (2023)
by: Kohl, Georg, et al.
Published: (2023)
Unfolding Time: Generative Modeling for Turbulent Flows in 4D
by: Saydemir, Abdullah, et al.
Published: (2024)
by: Saydemir, Abdullah, et al.
Published: (2024)
Vision-Informed Flow Image Super-Resolution with Quaternion Spatial Modeling and Dynamic Flow Convolution
by: Cao, Qinglong, et al.
Published: (2024)
by: Cao, Qinglong, et al.
Published: (2024)
Harnessing Equivariance: Modeling Turbulence with Graph Neural Networks
by: Kurz, Marius, et al.
Published: (2025)
by: Kurz, Marius, et al.
Published: (2025)
Physics-Informed Neural Network Approaches for Sparse Data Flow Reconstruction of Unsteady Flow Around Complex Geometries
by: Malineni, Vamsi Sai Krishna, et al.
Published: (2025)
by: Malineni, Vamsi Sai Krishna, et al.
Published: (2025)
From Zero to Turbulence: Generative Modeling for 3D Flow Simulation
by: Lienen, Marten, et al.
Published: (2023)
by: Lienen, Marten, et al.
Published: (2023)
Fusion-DeepONet: A Data-Efficient Neural Operator for Geometry-Dependent Hypersonic and Supersonic Flows
by: Peyvan, Ahmad, et al.
Published: (2025)
by: Peyvan, Ahmad, et al.
Published: (2025)
Active Control of Turbulent Airfoil Flows Using Adjoint-based Deep Learning
by: Liu, Xuemin, et al.
Published: (2025)
by: Liu, Xuemin, et al.
Published: (2025)
Quantifying Out-of-Training Uncertainty of Neural-Network based Turbulence Closures
by: Grogan, Cody, et al.
Published: (2025)
by: Grogan, Cody, et al.
Published: (2025)
Deep Learning-based Algebraic Reynolds Stress Closures for RANS Simulations of Turbulent Flows
by: Dehtyriov, Daniel, et al.
Published: (2026)
by: Dehtyriov, Daniel, et al.
Published: (2026)
Flow Field Reconstruction via Voronoi-Enhanced Physics-Informed Neural Networks with End-to-End Sensor Placement Optimization
by: Xiao, Renjie, et al.
Published: (2026)
by: Xiao, Renjie, et al.
Published: (2026)
Geometry-aware PINNs for Turbulent Flow Prediction
by: Ghosh, Shinjan, et al.
Published: (2024)
by: Ghosh, Shinjan, et al.
Published: (2024)
Learning Pore-scale Multi-phase Flow from Experimental Data with Graph Neural Network
by: Gu, Yuxuan, et al.
Published: (2024)
by: Gu, Yuxuan, et al.
Published: (2024)
CoNFiLD-inlet: Synthetic Turbulence Inflow Using Generative Latent Diffusion Models with Neural Fields
by: Liu, Xin-Yang, et al.
Published: (2024)
by: Liu, Xin-Yang, et al.
Published: (2024)
RiemannONets: Interpretable Neural Operators for Riemann Problems
by: Peyvan, Ahmad, et al.
Published: (2024)
by: Peyvan, Ahmad, et al.
Published: (2024)
Cross-Field Interface-Aware Neural Operators for Multiphase Flow Simulation
by: Wang, Zhenzhong, et al.
Published: (2025)
by: Wang, Zhenzhong, et al.
Published: (2025)
Fluids You Can Trust: Property-Preserving Operator Learning for Incompressible Flows
by: Sharma, Ramansh, et al.
Published: (2026)
by: Sharma, Ramansh, et al.
Published: (2026)
Predicting Time-Dependent Flow Over Complex Geometries Using Operator Networks
by: Rabeh, Ali, et al.
Published: (2025)
by: Rabeh, Ali, et al.
Published: (2025)
Improving the Robustness of Control of Chaotic Convective Flows with Domain-Informed Reinforcement Learning
by: Straat, Michiel, et al.
Published: (2025)
by: Straat, Michiel, et al.
Published: (2025)
Similar Items
-
The impact of observation density on Bayesian inversion of latent dynamics in shock-dominated flows
by: Tiwari, Bipin, et al.
Published: (2026) -
Implicit Augmentation from Distributional Symmetry in Turbulence Super-Resolution
by: Balla, Julia, et al.
Published: (2025) -
Shape Invariant 3D-Variational Autoencoder: Super Resolution in Turbulence flow
by: Maurya, Anuraj
Published: (2025) -
Spectrally Informed Learning of Fluid Flows
by: Shaffer, Benjamin D., et al.
Published: (2024) -
Integrating Neural Operators with Diffusion Models Improves Spectral Representation in Turbulence Modeling
by: Oommen, Vivek, et al.
Published: (2024)