The following pages link to (Q4938227):
Displaying 50 items.
- Approximation by max-product neural network operators of Kantorovich type (Q287317) (← links)
- Approximation by network operators with logistic activation functions (Q299680) (← links)
- Use of machine learning techniques to analyse the risk associated with mine sludge deposits (Q409805) (← links)
- A comparison between fixed-basis and variable-basis schemes for function approximation and functional optimization (Q411092) (← links)
- Accuracy of approximations of solutions to Fredholm equations by kernel methods (Q433295) (← links)
- Learning functions of few arbitrary linear parameters in high dimensions (Q434415) (← links)
- Approximation results for neural network operators activated by sigmoidal functions (Q459444) (← links)
- Multivariate neural network operators with sigmoidal activation functions (Q460677) (← links)
- On a method for constructing ensembles of regression models (Q462080) (← links)
- On the approximation by neural networks with bounded number of neurons in hidden layers (Q483038) (← links)
- The universal approximation capabilities of double \(2\pi\)-periodic approximate identity neural networks (Q521720) (← links)
- Suboptimal solutions to dynamic optimization problems via approximations of the policy functions (Q613579) (← links)
- Constructive approximate interpolation by neural networks in the metric space (Q623074) (← links)
- Approximation by neural networks with weights varying on a finite set of directions (Q663685) (← links)
- Learning non-parametric basis independent models from point queries via low-rank methods (Q741260) (← links)
- Entropy and sampling numbers of classes of ridge functions (Q745852) (← links)
- On sharpness of error bounds for univariate approximation by single hidden layer feedforward neural networks (Q777322) (← links)
- Overcoming the curse of dimensionality for some Hamilton-Jacobi partial differential equations via neural network architectures (Q783094) (← links)
- Approximative compactness of linear combinations of characteristic functions (Q783713) (← links)
- A representation problem for smooth sums of ridge functions (Q783716) (← links)
- Learning and generalization errors for the 2D binary perceptron. (Q815504) (← links)
- Constructive approximate interpolation by neural networks (Q817488) (← links)
- Interpolation and rates of convergence for a class of neural networks (Q840184) (← links)
- Geometric properties of the ridge function manifold (Q849339) (← links)
- Studying the performance of artificial neural networks on problems related to cryptography (Q867941) (← links)
- Comparing fixed and variable-width Gaussian networks (Q889280) (← links)
- On a smoothness problem in ridge function representation (Q900985) (← links)
- The construction and approximation of feedforward neural network with hyperbolic tangent function (Q904129) (← links)
- Approximation by polynomials and ridge functions of classes of \(s\)-monotone radial functions (Q927688) (← links)
- Convex polynomial and ridge approximation of Lipschitz functions in \(\mathbb R^d\) (Q983503) (← links)
- Hermite interpolation by neural networks (Q990455) (← links)
- Approximation schemes for functional optimization problems (Q1024253) (← links)
- Mathematics and neural networks -- A glance at some basic connections (Q1288752) (← links)
- Lower bounds for approximation by MLP neural networks (Q1305902) (← links)
- Best approximation by linear combinations of characteristic functions of half-spaces. (Q1395802) (← links)
- Approximation by neural networks with a bounded number of nodes at each level (Q1395810) (← links)
- Interpolation by ridge polynomials and its application in neural networks (Q1612364) (← links)
- Multivariate Jackson-type inequality for a new type neural network approximation (Q1634573) (← links)
- The universal approximation capabilities of cylindrical approximate identity neural networks (Q1639386) (← links)
- Solving numerically nonlinear systems of balance laws by multivariate sigmoidal functions approximation (Q1655363) (← links)
- Neural network operators: constructive interpolation of multivariate functions (Q1669090) (← links)
- Why does deep and cheap learning work so well? (Q1676557) (← links)
- Saturation classes for MAX-product neural network operators activated by sigmoidal functions (Q1682591) (← links)
- Mini-workshop: Deep learning and inverse problems. Abstracts from the mini-workshop held March 4--10, 2018 (Q1731979) (← links)
- Function approximation with zonal function networks with activation functions analogous to the rectified linear unit functions (Q1734693) (← links)
- Functional multi-layer perceptron: A nonlinear tool for functional data analysis (Q1763468) (← links)
- Some problems in the theory of ridge functions (Q1798075) (← links)
- A note on continuous sums of ridge functions (Q1801184) (← links)
- On best approximation of classes by radial functions (Q1867260) (← links)
- Approximation rates for neural networks with general activation functions (Q1982446) (← links)
