:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Quattromini, M., Bucci, M. A., Cherubini, S., Semeraro, O.
Format:	Preprint
Published:	2024
Subjects:	Fluid Dynamics Machine Learning
Online Access:	https://arxiv.org/abs/2411.09476
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Active learning of data-assimilation closures using Graph Neural Networks
by: Quattromini, Michele, et al.
Published: (2023)

Neural ensemble Kalman filter: Data assimilation for compressible flows with shocks
by: Zhou, Xu-Hui, et al.
Published: (2026)

Unsupervised simulation of incompressible flows with physics- and equality- constrained artificial neural networks
by: Hu, Qifeng, et al.
Published: (2025)

Data assimilation and parameter identification for water waves using the nonlinear Schrödinger equation and physics-informed neural networks
by: Ehlers, Svenja, et al.
Published: (2024)

Reconstructing unsteady flows from sparse, noisy measurements with a physics-constrained convolutional neural network
by: Mo, Yaxin, et al.
Published: (2024)

Invariant Control Strategies for Active Flow Control using Graph Neural Networks
by: Kurz, Marius, et al.
Published: (2025)

Online model learning with data-assimilated reservoir computers
by: Nóvoa, Andrea, et al.
Published: (2025)

Multi-fidelity physics constrained neural networks for dynamical systems
by: Zhou, Hao, et al.
Published: (2024)

Physics-constrained coupled neural differential equations for one dimensional blood flow modeling
by: Csala, Hunor, et al.
Published: (2024)

Harnessing Equivariance: Modeling Turbulence with Graph Neural Networks
by: Kurz, Marius, et al.
Published: (2025)

FIGNN: Feature-Specific Interpretability for Graph Neural Network Surrogate Models
by: Raut, Riddhiman, et al.
Published: (2025)

MeshMask: Physics-Based Simulations with Masked Graph Neural Networks
by: Garnier, Paul, et al.
Published: (2025)

MENO: MeanFlow-Enhanced Neural Operators for Dynamical Systems
by: Yang, Tianyue, et al.
Published: (2026)

Can physical information aid the generalization ability of Neural Networks for hydraulic modeling?
by: Guglielmo, Gianmarco, et al.
Published: (2024)

Predicting Energy Budgets in Droplet Dynamics: A Recurrent Neural Network Approach
by: de Aguiar, Diego A., et al.
Published: (2024)

Analysis of tidal flows through the Strait of Gibraltar using Dynamic Mode Decomposition
by: Dias, Sathsara, et al.
Published: (2023)

Learning Pore-scale Multi-phase Flow from Experimental Data with Graph Neural Network
by: Gu, Yuxuan, et al.
Published: (2024)

Physics-Informed Graph Neural Network Surrogates for Turbulent Nanoparticle Dispersion in Dental Clinical Environments
by: Shende, Takshak, et al.
Published: (2026)

Physics-informed neural networks for phase-resolved data assimilation and prediction of nonlinear ocean waves
by: Ehlers, Svenja, et al.
Published: (2025)

Equation identification for fluid flows via physics-informed neural networks
by: New, Alexander, et al.
Published: (2024)

Prediction of flow and elastic stresses in a viscoelastic turbulent channel flow using convolutional neural networks
by: Balasubramanian, Arivazhagan G., et al.
Published: (2024)

Differentiable Turbulence: Closure as a partial differential equation constrained optimization
by: Shankar, Varun, et al.
Published: (2023)

Identifying recurrent flows in high-dimensional dissipative chaos from low-dimensional embeddings
by: Beck, Pierre, et al.
Published: (2026)

Distributed physics-informed neural networks via domain decomposition for fast flow reconstruction
by: Qian, Yixiao, et al.
Published: (2026)

Equation-informed data-driven identification of flow budgets and dynamics
by: Sevryugina, Nataliya, et al.
Published: (2024)

HFNO: an interpretable data-driven decomposition strategy for turbulent flows
by: Cayuela, Marco, et al.
Published: (2025)

Generative prediction of flow fields around an obstacle using the diffusion model
by: Hu, Jiajun, et al.
Published: (2024)

Physics-constrained convolutional neural networks for inverse problems in spatiotemporal partial differential equations
by: Kelshaw, Daniel, et al.
Published: (2024)

On the joint estimation of flow fields and particle properties from Lagrangian data
by: Zhou, Ke, et al.
Published: (2025)

Reduced-order modeling of unsteady fluid flow using neural network ensembles
by: Halder, Rakesh, et al.
Published: (2024)

An ALE-Consistent Graph Neural Operator-Transformer Framework for Fluid-Structure Interaction
by: Zhao, Shihang, et al.
Published: (2026)

Bayesian Reasoning for Physics Informed Neural Networks
by: Graczyk, Krzysztof M., et al.
Published: (2023)

Efficient temporal prediction of compressible flows in irregular domains using Fourier neural operators
by: Nie, Yifan, et al.
Published: (2026)

Super-resolution of turbulent reacting flows on complex meshes using graph neural networks
by: Dash, Priyabrat, et al.
Published: (2026)

Physics-constrained DeepONet for Surrogate CFD models: a curved backward-facing step case
by: Jnini, Anas, et al.
Published: (2025)

Hard Constraint Projection in a Physics Informed Neural Network
by: Horne, Miranda J. S., et al.
Published: (2026)

Parametric Dynamic Mode Decomposition with multi-linear interpolation for prediction of thermal fields of Al2O3-water nanofluid flows at unseen parameters
by: S, Abhijith M, et al.
Published: (2025)

Interpretable A-posteriori Error Indication for Graph Neural Network Surrogate Models
by: Barwey, Shivam, et al.
Published: (2023)

Update hydrological states or meteorological forcings? Comparing data assimilation methods for differentiable hydrologic models
by: Jamaat, Amirmoez, et al.
Published: (2025)

Periodicity-Enforced Neural Network for Designing Deterministic Lateral Displacement Devices
by: Lee, Andrew, et al.
Published: (2025)