Pages that link to "Item:Q726815"
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The following pages link to Machine learning strategies for systems with invariance properties (Q726815):
Displaying 20 items.
- Mean Field Analysis of Neural Networks: A Law of Large Numbers (Q5219306) (← links)
- A neural network approach for the blind deconvolution of turbulent flows (Q5231546) (← links)
- Reynolds averaged turbulence modelling using deep neural networks with embedded invariance (Q5360504) (← links)
- Sub-grid scale model classification and blending through deep learning (Q5379089) (← links)
- Machine Learning and Invariant Theory (Q6049160) (← links)
- Comparison of different data-assimilation approaches to augment RANS turbulence models (Q6060768) (← links)
- Material modeling for parametric, anisotropic finite strain hyperelasticity based on machine learning with application in optimization of metamaterials (Q6061746) (← links)
- Advanced discretization techniques for hyperelastic physics-augmented neural networks (Q6062433) (← links)
- Exact conservation laws for neural network integrators of dynamical systems (Q6105087) (← links)
- Deep learning closure models for large-eddy simulation of flows around bluff bodies (Q6114185) (← links)
- A highly accurate strategy for data-driven turbulence modeling (Q6125393) (← links)
- Data-driven wall modeling for turbulent separated flows (Q6158122) (← links)
- Evaluation of physics constrained data-driven methods for turbulence model uncertainty quantification (Q6158540) (← links)
- Normalization effects on deep neural networks (Q6194477) (← links)
- A probabilistic, data-driven closure model for RANS simulations with aleatoric, model uncertainty (Q6553801) (← links)
- Data-driven approach for modeling Reynolds stress tensor with invariance preservation (Q6566931) (← links)
- Deep learning in computational mechanics: a review (Q6604128) (← links)
- Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response (Q6641865) (← links)
- Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models (Q6641896) (← links)
- Neural operator based Reynolds averaged turbulence modelling (Q6647989) (← links)
