Pages that link to "Item:Q5079533"
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The following pages link to Deep ReLU Networks Overcome the Curse of Dimensionality for Generalized Bandlimited Functions (Q5079533):
Displaying 19 items.
- Error bounds for deep ReLU networks using the Kolmogorov-Arnold superposition theorem (Q2055036) (← links)
- High-dimensional distribution generation through deep neural networks (Q2062235) (← links)
- Optimal approximation rate of ReLU networks in terms of width and depth (Q2065073) (← links)
- SelectNet: self-paced learning for high-dimensional partial differential equations (Q2131038) (← links)
- ReLU deep neural networks from the hierarchical basis perspective (Q2159911) (← links)
- Active learning based sampling for high-dimensional nonlinear partial differential equations (Q2683063) (← links)
- The Discovery of Dynamics via Linear Multistep Methods and Deep Learning: Error Estimation (Q5096451) (← links)
- A note on the applications of one primary function in deep neural networks (Q5097859) (← links)
- A note on the expressive power of deep rectified linear unit networks in high‐dimensional spaces (Q5223573) (← links)
- Stationary Density Estimation of Itô Diffusions Using Deep Learning (Q5886225) (← links)
- Approximation bounds for norm constrained neural networks with applications to regression and GANs (Q6038825) (← links)
- Deep Neural Networks for Solving Large Linear Systems Arising from High-Dimensional Problems (Q6054285) (← links)
- Friedrichs Learning: Weak Solutions of Partial Differential Equations via Deep Learning (Q6108164) (← links)
- Deep Neural Networks with ReLU-Sine-Exponential Activations Break Curse of Dimensionality in Approximation on Hölder Class (Q6137593) (← links)
- Neural network approximation and estimation of classifiers with classification boundary in a Barron class (Q6165247) (← links)
- Approximation in shift-invariant spaces with deep ReLU neural networks (Q6341347) (← links)
- Solving PDEs on unknown manifolds with machine learning (Q6499004) (← links)
- Deep ReLU networks and high-order finite element methods. II: Chebyšev emulation (Q6585367) (← links)
- Solving PDEs on spheres with physics-informed convolutional neural networks (Q6652574) (← links)
