Pages that link to "Item:Q2149063"
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The following pages link to Error estimates for deep learning methods in fluid dynamics (Q2149063):
Displaying 9 items.
- Error bounds of the invariant statistics in machine learning of ergodic Itô diffusions (Q2077623) (← links)
- A priori and a posteriori error estimates for the deep Ritz method applied to the Laplace and Stokes problem (Q2095152) (← links)
- Deep-learning accelerated calculation of real-fluid properties in numerical simulation of complex flowfields (Q2132659) (← links)
- Scientific machine learning through physics-informed neural networks: where we are and what's next (Q2162315) (← links)
- Structure preservation for the deep neural network multigrid solver (Q2672194) (← links)
- Some elliptic second order problems and neural network solutions: existence and error estimates (Q6073185) (← links)
- Physics-informed neural networks for approximating dynamic (hyperbolic) PDEs of second order in time: error analysis and algorithms (Q6087958) (← links)
- Error estimates and physics informed augmentation of neural networks for thermally coupled incompressible Navier Stokes equations (Q6109270) (← links)
- Higher-order error estimates for physics-informed neural networks approximating the primitive equations (Q6114171) (← links)
