Pages that link to "Item:Q2245362"
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The following pages link to Output-based adaptive aerodynamic simulations using convolutional neural networks (Q2245362):
Displaying 9 items.
- A deep learning approach for the transonic flow field predictions around airfoils (Q2670066) (← links)
- Surrogate convolutional neural network models for steady computational fluid dynamics simulations (Q2672202) (← links)
- Output-based error estimation and mesh adaptation for unsteady turbulent flow simulations (Q2674074) (← links)
- Mesh optimization using an improved self-organizing mechanism (Q6082343) (← links)
- Physics-informed deep learning for simultaneous surrogate modeling and PDE-constrained optimization of an airfoil geometry (Q6097587) (← links)
- Quasi-optimal \textit{hp}-finite element refinements towards singularities via deep neural network prediction (Q6103655) (← links)
- Learning Robust Marking Policies for Adaptive Mesh Refinement (Q6189171) (← links)
- SuperAdjoint: super-resolution neural networks in adjoint-based error estimation (Q6489238) (← links)
- DynAMO: multi-agent reinforcement learning for dynamic anticipatory mesh optimization with applications to hyperbolic conservation laws (Q6498465) (← links)
