Learning solutions of parametric Navier-Stokes with physics-informed neural networks
Fuente:
arXiv
Guardado en:
| Autores principales: | Naderibeni, M., Reinders, M. J. T., Wu, L., Tax, D. M. J. |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Accelerated and data-efficient flow prediction in stirred tanks via physics-informed learning
por: Naderibeni, Mahdi, et al.
Publicado: (2026)
por: Naderibeni, Mahdi, et al.
Publicado: (2026)
Physics-informed neural networks for parameter learning of wildfire spreading
por: Vogiatzoglou, Konstantinos, et al.
Publicado: (2024)
por: Vogiatzoglou, Konstantinos, et al.
Publicado: (2024)
Transfer learning-based physics-informed convolutional neural network for simulating flow in porous media with time-varying controls
por: Chen, Jungang, et al.
Publicado: (2023)
por: Chen, Jungang, et al.
Publicado: (2023)
Integration of physics-informed operator learning and finite element method for parametric learning of partial differential equations
por: Rezaei, Shahed, et al.
Publicado: (2024)
por: Rezaei, Shahed, et al.
Publicado: (2024)
Energy-based physics-informed neural network for frictionless contact problems under large deformation
por: Bai, Jinshuai, et al.
Publicado: (2024)
por: Bai, Jinshuai, et al.
Publicado: (2024)
Fast training of accurate physics-informed neural networks without gradient descent
por: Datar, Chinmay, et al.
Publicado: (2024)
por: Datar, Chinmay, et al.
Publicado: (2024)
Convergence of physics-informed neural networks modeling time-harmonic wave fields
por: Schoder, Stefan, et al.
Publicado: (2025)
por: Schoder, Stefan, et al.
Publicado: (2025)
Data-driven building energy efficiency prediction using physics-informed neural networks
por: Michalakopoulos, Vasilis, et al.
Publicado: (2023)
por: Michalakopoulos, Vasilis, et al.
Publicado: (2023)
Local learning for stable backpropagation-free neural network training towards physical learning
por: Guo, Yaqi, et al.
Publicado: (2026)
por: Guo, Yaqi, et al.
Publicado: (2026)
Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models
por: Padmanabha, Govinda Anantha, et al.
Publicado: (2024)
por: Padmanabha, Govinda Anantha, et al.
Publicado: (2024)
Deep encoder-decoder hierarchical convolutional neural networks for conjugate heat transfer surrogate modeling
por: Ebbs-Picken, Takiah, et al.
Publicado: (2023)
por: Ebbs-Picken, Takiah, et al.
Publicado: (2023)
On instabilities in neural network-based physics simulators
por: Floryan, Daniel
Publicado: (2024)
por: Floryan, Daniel
Publicado: (2024)
Detecting hidden structures from a static loading experiment: topology optimization meets physics-informed neural networks
por: Mowlavi, Saviz, et al.
Publicado: (2023)
por: Mowlavi, Saviz, et al.
Publicado: (2023)
Simulation of parametrized cardiac electrophysiology in three dimensions using physics-informed neural networks
por: Gomez, Roshan Antony, et al.
Publicado: (2025)
por: Gomez, Roshan Antony, et al.
Publicado: (2025)
A Dual-Path neural network model to construct the flame nonlinear thermoacoustic response in the time domain
por: Wu, Jiawei, et al.
Publicado: (2024)
por: Wu, Jiawei, et al.
Publicado: (2024)
Predicting the fatigue life of asphalt concrete using neural networks
por: Houlík, Jakub, et al.
Publicado: (2024)
por: Houlík, Jakub, et al.
Publicado: (2024)
Discovering uncertainty: Gaussian constitutive neural networks with correlated weights
por: McCulloch, Jeremy A., et al.
Publicado: (2025)
por: McCulloch, Jeremy A., et al.
Publicado: (2025)
Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric space
por: Koopas, Rasoul Najafi, et al.
Publicado: (2024)
por: Koopas, Rasoul Najafi, et al.
Publicado: (2024)
Aerodynamic force reconstruction using physics-informed Gaussian processes
por: Tondo, Gledson Rodrigo, et al.
Publicado: (2026)
por: Tondo, Gledson Rodrigo, et al.
Publicado: (2026)
Interpreting core forms of urban morphology linked to urban functions with explainable graph neural network
por: Chen, Dongsheng, et al.
Publicado: (2025)
por: Chen, Dongsheng, et al.
Publicado: (2025)
Simultaneous solution of incompressible Navier-Stokes flows on multiple surfaces
por: Kaiser, Michael Wolfgang, et al.
Publicado: (2025)
por: Kaiser, Michael Wolfgang, et al.
Publicado: (2025)
Physics-informed solution reconstruction in elasticity and heat transfer using the explicit constraint force method
por: Rowan, Conor, et al.
Publicado: (2025)
por: Rowan, Conor, et al.
Publicado: (2025)
PINN-MG: A physics-informed neural network for mesh generation
por: Wang, Min, et al.
Publicado: (2025)
por: Wang, Min, et al.
Publicado: (2025)
Interpretable long-term traffic modelling on national road networks using theory-informed deep learning
por: Li, Yue, et al.
Publicado: (2026)
por: Li, Yue, et al.
Publicado: (2026)
Automated machine learning for physics-informed convolutional neural networks
por: Zhou, Wanyun, et al.
Publicado: (2024)
por: Zhou, Wanyun, et al.
Publicado: (2024)
Cross-attention-based bipartite graph neural network for coupled nodal and elemental field prediction in large-deformation sheet material forming
por: Zhao, Yingxue, et al.
Publicado: (2026)
por: Zhao, Yingxue, et al.
Publicado: (2026)
A parametric framework for kernel-based dynamic mode decomposition using deep learning
por: Kevopoulos, Konstantinos, et al.
Publicado: (2024)
por: Kevopoulos, Konstantinos, et al.
Publicado: (2024)
A TVD neural network closure and application to turbulent combustion
por: Suh, Seung Won, et al.
Publicado: (2024)
por: Suh, Seung Won, et al.
Publicado: (2024)
Importance of localized dilatation and distensibility in identifying determinants of thoracic aortic aneurysm with neural operators
por: Li, David S., et al.
Publicado: (2025)
por: Li, David S., et al.
Publicado: (2025)
Graph neural network-based surrogate modelling for real-time hydraulic prediction of urban drainage networks
por: Zhang, Zhiyu, et al.
Publicado: (2024)
por: Zhang, Zhiyu, et al.
Publicado: (2024)
Surface profile recovery from electromagnetic field with physics--informed neural networks
por: Chen, Yuxuan, et al.
Publicado: (2024)
por: Chen, Yuxuan, et al.
Publicado: (2024)
Physics-informed Deep Learning to Solve Three-dimensional Terzaghi Consolidation Equation: Forward and Inverse Problems
por: Yuan, Biao, et al.
Publicado: (2024)
por: Yuan, Biao, et al.
Publicado: (2024)
UQ-SHRED: uncertainty quantification of shallow recurrent decoder networks for sparse sensing via engression
por: Gao, Mars Liyao, et al.
Publicado: (2026)
por: Gao, Mars Liyao, et al.
Publicado: (2026)
A nonlinear extension of parametric model embedding for dimensionality reduction in parametric shape design
por: Serani, Andrea, et al.
Publicado: (2026)
por: Serani, Andrea, et al.
Publicado: (2026)
Machine Learning based Prediction of Ditching Loads
por: Schwarz, Henning, et al.
Publicado: (2024)
por: Schwarz, Henning, et al.
Publicado: (2024)
BO-SA-PINNs: Self-adaptive physics-informed neural networks based on Bayesian optimization for automatically designing PDE solvers
por: Zhang, Rui, et al.
Publicado: (2025)
por: Zhang, Rui, et al.
Publicado: (2025)
DynBERG: Dynamic BERT-based Graph neural network for financial fraud detection
por: Kulkarni, Omkar, et al.
Publicado: (2025)
por: Kulkarni, Omkar, et al.
Publicado: (2025)
Purpose in the Machine: Do Traffic Simulators Produce Distributionally Equivalent Outcomes for Reinforcement Learning Applications?
por: Chen, Rex, et al.
Publicado: (2023)
por: Chen, Rex, et al.
Publicado: (2023)
Discovering interpretable elastoplasticity models via the neural polynomial method enabled symbolic regressions
por: Bahmani, Bahador, et al.
Publicado: (2023)
por: Bahmani, Bahador, et al.
Publicado: (2023)
LatticeGraphNet: A two-scale graph neural operator for simulating lattice structures
por: Jain, Ayush, et al.
Publicado: (2024)
por: Jain, Ayush, et al.
Publicado: (2024)
Ejemplares similares
-
Accelerated and data-efficient flow prediction in stirred tanks via physics-informed learning
por: Naderibeni, Mahdi, et al.
Publicado: (2026) -
Physics-informed neural networks for parameter learning of wildfire spreading
por: Vogiatzoglou, Konstantinos, et al.
Publicado: (2024) -
Transfer learning-based physics-informed convolutional neural network for simulating flow in porous media with time-varying controls
por: Chen, Jungang, et al.
Publicado: (2023) -
Integration of physics-informed operator learning and finite element method for parametric learning of partial differential equations
por: Rezaei, Shahed, et al.
Publicado: (2024) -
Energy-based physics-informed neural network for frictionless contact problems under large deformation
por: Bai, Jinshuai, et al.
Publicado: (2024)