Pages that link to "Item:Q6068269"
From MaRDI portal
The following pages link to Combining machine learning and domain decomposition methods for the solution of partial differential equations—A review (Q6068269):
Displaying 17 items.
- A general-purpose machine learning framework for predicting singular integrals in boundary element method (Q785081) (← links)
- Spectral coarse spaces for the substructured parallel Schwarz method (Q2148134) (← links)
- Three ways to solve partial differential equations with neural networks — A review (Q6068232) (← links)
- An overlapping domain decomposition method for the solution of parametric elliptic problems via proper generalized decomposition (Q6118540) (← links)
- A new method for solving nonlinear partial differential equations based on liquid time-constant networks (Q6130983) (← links)
- Finite basis physics-informed neural networks (FBPINNs): a scalable domain decomposition approach for solving differential equations (Q6171723) (← links)
- Learning adaptive coarse basis functions of FETI-DP (Q6198156) (← links)
- Physical informed memory networks for solving PDEs: implementation and applications (Q6497869) (← links)
- Adaptive deep Fourier residual method via overlapping domain decomposition (Q6557761) (← links)
- Physics-informed parallel neural networks with self-adaptive loss weighting for the identification of continuous structural systems (Q6557810) (← links)
- Domain decomposition learning methods for solving elliptic problems (Q6585310) (← links)
- Multilevel domain decomposition-based architectures for physics-informed neural networks (Q6588267) (← links)
- Iterative algorithms for partitioned neural network approximation to partial differential equations (Q6590244) (← links)
- A domain decomposition-based CNN-DNN architecture for model parallel training applied to image recognition problems (Q6598498) (← links)
- Predicting the geometric location of critical edges in adaptive GDSW overlapping domain decomposition methods using deep learning (Q6630127) (← links)
- Discovering artificial viscosity models for discontinuous Galerkin approximation of conservation laws using physics-informed machine learning (Q6648381) (← links)
- Adaptive deep density approximation for stochastic dynamical systems (Q6671865) (← links)
