Pages that link to "Item:Q3399370"
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The following pages link to An Integral Upper Bound for Neural Network Approximation (Q3399370):
Displaying 16 items.
- Approximation by max-product neural network operators of Kantorovich type (Q287317) (← links)
- On the tractability of multivariate integration and approximation by neural networks (Q876822) (← links)
- Approximation theorems for a family of multivariate neural network operators in Orlicz-type spaces (Q1623021) (← links)
- Saturation classes for MAX-product neural network operators activated by sigmoidal functions (Q1682591) (← links)
- Complexity estimates based on integral transforms induced by computational units (Q1941596) (← links)
- A tight upper bound on the generalization error of feedforward neural networks (Q1982395) (← links)
- Asymptotic expansion for neural network operators of the Kantorovich type and high order of approximation (Q2023320) (← links)
- Piecewise convexity of artificial neural networks (Q2292218) (← links)
- The construction and approximation of the neural network with two weights (Q2336809) (← links)
- Convergence for a family of neural network operators in Orlicz spaces (Q2965304) (← links)
- Integral combinations of Heavisides (Q3567445) (← links)
- Convergence results for a family of Kantorovich max-product neural network operators in a multivariate setting (Q4599380) (← links)
- A Framework for the Construction of Upper Bounds on the Number of Affine Linear Regions of ReLU Feed-Forward Neural Networks (Q5211507) (← links)
- Measure Theoretic Results for Approximation by Neural Networks with Limited Weights (Q5365276) (← links)
- Continuous limits of residual neural networks in case of large input data (Q6098879) (← links)
- Lower bounds for artificial neural network approximations: a proof that shallow neural networks fail to overcome the curse of dimensionality (Q6155895) (← links)
