Pages that link to "Item:Q6069455"
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The following pages link to Linearized Learning with Multiscale Deep Neural Networks for Stationary Navier-Stokes Equations with Oscillatory Solutions (Q6069455):
Displaying 7 items.
- Physics-Driven Learning of the Steady Navier-Stokes Equations using Deep Convolutional Neural Networks (Q5042008) (← links)
- Multi-Scale Deep Neural Network (MscaleDNN) Methods for Oscillatory Stokes Flows in Complex Domains (Q5162374) (← links)
- Using deep neural networks for detecting spurious oscillations in discontinuous Galerkin solutions of convection-dominated convection-diffusion equations (Q6080848) (← links)
- Asymptotic-preserving neural networks for multiscale time-dependent linear transport equations (Q6158979) (← links)
- Adaptive sampling points based multi-scale residual network for solving partial differential equations (Q6585372) (← links)
- Machine learning algorithm for the Monge-Ampère equation with transport boundary conditions (Q6630933) (← links)
- Efficiently training physics-informed neural networks via anomaly-aware optimization (Q6662394) (← links)
