Pages that link to "Item:Q2157922"
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The following pages link to Approximation properties of deep ReLU CNNs (Q2157922):
Displaying 19 items.
- The universal approximation property. Characterization, construction, representation, and existence (Q2043428) (← links)
- Constructive deep ReLU neural network approximation (Q2067309) (← links)
- Approximation spaces of deep neural networks (Q2117336) (← links)
- ReLU deep neural networks from the hierarchical basis perspective (Q2159911) (← links)
- ReLU Networks Are Universal Approximators via Piecewise Linear or Constant Functions (Q3386431) (← links)
- Lipschitz properties for deep convolutional networks (Q4686249) (← links)
- Deep Neural Network Approximation Theory (Q5001568) (← links)
- Deep ReLU Networks Overcome the Curse of Dimensionality for Generalized Bandlimited Functions (Q5079533) (← links)
- Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks (Q5162362) (← links)
- On minimal representations of shallow ReLU networks (Q6072445) (← links)
- Towards Lower Bounds on the Depth of ReLU Neural Networks (Q6100606) (← links)
- MorphoActivation: generalizing ReLU activation function by mathematical morphology (Q6103070) (← links)
- A Note on the Regularity of Images Generated by Convolutional Neural Networks (Q6136232) (← links)
- Error bounds for approximations using multichannel deep convolutional neural networks with downsampling (Q6155792) (← links)
- Approximation in shift-invariant spaces with deep ReLU neural networks (Q6341347) (← links)
- An Interpretive Constrained Linear Model for ResNet and MgNet (Q6385646) (← links)
- Approximation of classifiers by deep perceptron networks (Q6488832) (← links)
- Approximation analysis of CNNs from a feature extraction view (Q6496341) (← links)
- An enhanced V-cycle MgNet model for operator learning in numerical partial differential equations (Q6662449) (← links)
