Pages that link to "Item:Q2127017"
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The following pages link to NSFnets (Navier-Stokes flow nets): physics-informed neural networks for the incompressible Navier-Stokes equations (Q2127017):
Displaying 7 items.
- Prediction of spatiotemporal dynamics using deep learning: coupled neural networks of long short-terms memory, auto-encoder and physics-informed neural networks (Q6650113) (← links)
- Approximating families of sharp solutions to Fisher's equation with physics-informed neural networks (Q6660246) (← links)
- Simple yet effective adaptive activation functions for physics-informed neural networks (Q6660250) (← links)
- Analysis of deep Ritz methods for semilinear elliptic equations (Q6662390) (← links)
- NeuroSEM: a hybrid framework for simulating multiphysics problems by coupling PINNs and spectral elements (Q6663315) (← links)
- An implicit GNN solver for Poisson-like problems (Q6663428) (← links)
- Annealed adaptive importance sampling method in PINNs for solving high dimensional partial differential equations (Q6670734) (← links)
