Pages that link to "Item:Q2679332"
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The following pages link to Neural control of discrete weak formulations: Galerkin, least squares \& minimal-residual methods with quasi-optimal weights (Q2679332):
Displaying 9 items.
- Optimally weighted loss functions for solving PDEs with neural networks (Q2068635) (← links)
- Galerkin neural network approximation of singularly-perturbed elliptic systems (Q2679286) (← links)
- A deep double Ritz method (\(\mathrm{D^2RM}\)) for solving partial differential equations using neural networks (Q2683471) (← links)
- \(r\)-adaptive deep learning method for solving partial differential equations (Q6144172) (← links)
- DNN-MG: a hybrid neural network/finite element method with applications to 3D simulations of the Navier-Stokes equations (Q6194150) (← links)
- Neural Control of Discrete Weak Formulations: Galerkin, Least-Squares and Minimal-Residual Methods with Quasi-Optimal Weights (Q6402170) (← links)
- Robust variational physics-informed neural networks (Q6497138) (← links)
- Learning quantities of interest from parametric PDEs: an efficient neural-weighted minimal residual approach (Q6543646) (← links)
- Neural network quaternion-based controller for port-Hamiltonian system (Q6553527) (← links)
