Pages that link to "Item:Q483038"

The following pages link to On the approximation by neural networks with bounded number of neurons in hidden layers (Q483038):

Displaying 42 items.

• Approximation by max-product neural network operators of Kantorovich type (Q287317) (← links)
• Function approximation by random neural networks with a bounded number of layers (Q996694) (← links)
• Bounds on the learning capacity of some multi-layer networks (Q1115371) (← links)
• Approximation by Ridge functions and neural networks with one hidden layer (Q1198148) (← links)
• Lower bounds for approximation by MLP neural networks (Q1305902) (← links)
• Bounds on the number of units for computing arbitrary dichotomies by multilayer perceptrons (Q1319352) (← links)
• Approximation by neural networks with a bounded number of nodes at each level (Q1395810) (← links)
• A better approximation for balls (Q1577916) (← links)
• The hidden layer size in feed-forward neural networks: A statistical point of view (Q1606011) (← links)
• Approximation theorems for a family of multivariate neural network operators in Orlicz-type spaces (Q1623021) (← links)
• The universal approximation capabilities of cylindrical approximate identity neural networks (Q1639386) (← links)
• Neural network operators: constructive interpolation of multivariate functions (Q1669090) (← links)
• Saturation classes for MAX-product neural network operators activated by sigmoidal functions (Q1682591) (← links)
• Limitations of the approximation capabilities of neural networks with one hidden layer (Q1923890) (← links)
• Asymptotic expansion for neural network operators of the Kantorovich type and high order of approximation (Q2023320) (← links)
• Two-hidden-layer feed-forward networks are universal approximators: a constructive approach (Q2057712) (← links)
• Robust and resource-efficient identification of two hidden layer neural networks (Q2117339) (← links)
• Voronovskaja type theorems and high-order convergence neural network operators with sigmoidal functions (Q2178844) (← links)
• On the approximation by single hidden layer feedforward neural networks with fixed weights (Q2179313) (← links)
• Negative results for approximation using single layer and multilayer feedforward neural networks (Q2226355) (← links)
• Limitations of shallow nets approximation (Q2292226) (← links)
• On a problem of Hornik (Q2354173) (← links)
• Almost everywhere approximation capabilities of double Mellin approximate identity neural networks (Q2403275) (← links)
• Pointwise and uniform approximation by multivariate neural network operators of the max-product type (Q2418225) (← links)
• Max-product neural network and quasi-interpolation operators activated by sigmoidal functions (Q2630379) (← links)
• Asymptotic expansions and Voronovskaja type theorems for the multivariate neural network operators (Q2668573) (← links)
• A three layer neural network can represent any multivariate function (Q2697707) (← links)
• On submanifolds of highly negatively curved spaces (Q2874681) (← links)
• A note on neural networks for optimal approximation of continuous functions in \(\mathbb{R}^d\) (Q2923568) (← links)
• Convergence for a family of neural network operators in Orlicz spaces (Q2965304) (← links)
• Approximation by ridge functions and neural networks with a bounded number of neurons (Q3452446) (← links)
• (Q4220209) (← links)
• Dimension-independent bounds on the degree of approximation by neural networks (Q4320794) (← links)
• Approximation Capability of Layered Neural Networks with Sigmoid Units on Two Layers (Q4323349) (← 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)
• A Single Hidden Layer Feedforward Network with Only One Neuron in the Hidden Layer Can Approximate Any Univariate Function (Q5380543) (← links)
• An adaptive learning rate backpropagation‐type neural network for solving <b><i>n</i> × <i>n</i></b> systems on nonlinear algebraic equations (Q5739238) (← links)
• Approximation capabilities of neural networks on unbounded domains (Q6055159) (← links)
• Approximating smooth and sparse functions by deep neural networks: optimal approximation rates and saturation (Q6062170) (← links)
• Lower bounds for artificial neural network approximations: a proof that shallow neural networks fail to overcome the curse of dimensionality (Q6155895) (← links)
• Approximation results by multivariate Kantorovich-type neural network sampling operators in Lebesgue spaces with variable exponents (Q6562343) (← links)