Pages that link to "Item:Q2131038"
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The following pages link to SelectNet: self-paced learning for high-dimensional partial differential equations (Q2131038):
Displaying 16 items.
- Neural networks enforcing physical symmetries in nonlinear dynamical lattices: the case example of the Ablowitz-Ladik model (Q2140106) (← links)
- A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks (Q2679440) (← links)
- DAS-PINNs: a deep adaptive sampling method for solving high-dimensional partial differential equations (Q2681099) (← links)
- Active learning based sampling for high-dimensional nonlinear partial differential equations (Q2683063) (← links)
- Stationary Density Estimation of Itô Diffusions Using Deep Learning (Q5886225) (← links)
- Simultaneous neural network approximation for smooth functions (Q6052416) (← links)
- A priori generalization error analysis of two-layer neural networks for solving high dimensional Schrödinger eigenvalue problems (Q6076649) (← links)
- Artificial neural network solver for time-dependent Fokker-Planck equations (Q6096280) (← links)
- Gradient and uncertainty enhanced sequential sampling for global fit (Q6096471) (← links)
- Friedrichs Learning: Weak Solutions of Partial Differential Equations via Deep Learning (Q6108164) (← links)
- Deep Ritz method for elliptical multiple eigenvalue problems (Q6182319) (← links)
- SelectNet: Self-paced Learning for High-dimensional Partial Differential Equations (Q6332866) (← links)
- Gauss Newton method for solving variational problems of PDEs with neural network discretizaitons (Q6569679) (← links)
- Applications of finite difference-based physics-informed neural networks to steady incompressible isothermal and thermal flows (Q6570872) (← links)
- A gradient-enhanced physics-informed neural networks method for the wave equation (Q6583846) (← links)
- Efficiently training physics-informed neural networks via anomaly-aware optimization (Q6662394) (← links)
