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2011.09363
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Neural network approximation and estimation of classifiers with classification boundary in a Barron class
The Annals of Applied Probability (Ann. Appl. Probab.), 2020
18 November 2020
A. Caragea
P. Petersen
F. Voigtlaender
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Papers citing
"Neural network approximation and estimation of classifiers with classification boundary in a Barron class"
24 / 24 papers shown
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On Excess Risk Convergence Rates of Neural Network Classifiers
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Embedding Inequalities for Barron-type Spaces
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30 May 2023
Embeddings between Barron spaces with higher order activation functions
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L
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L^p
L
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sampling numbers for the Fourier-analytic Barron space
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146
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Optimal learning of high-dimensional classification problems using deep neural networks
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343
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Integral representations of shallow neural network with Rectified Power Unit activation function
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Sobolev-type embeddings for neural network approximation spaces
Constructive approximation (Constr. Approx.), 2021
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Stationary Density Estimation of Itô Diffusions Using Deep Learning
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Senwei Liang
Haizhao Yang
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Random feature neural networks learn Black-Scholes type PDEs without curse of dimensionality
Journal of machine learning research (JMLR), 2021
Lukas Gonon
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A Priori Generalization Error Analysis of Two-Layer Neural Networks for Solving High Dimensional Schrödinger Eigenvalue Problems
Communications of the American Mathematical Society (Comm. Amer. Math. Soc.), 2021
Jianfeng Lu
Yulong Lu
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04 May 2021
Proof of the Theory-to-Practice Gap in Deep Learning via Sampling Complexity bounds for Neural Network Approximation Spaces
Foundations of Computational Mathematics (FoCM), 2021
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254
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06 Apr 2021
Some observations on high-dimensional partial differential equations with Barron data
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Stephan Wojtowytsch
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Learning Sub-Patterns in Piecewise Continuous Functions
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Behnoosh Zamanlooy
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Representation formulas and pointwise properties for Barron functions
Calculus of Variations and Partial Differential Equations (Calc. Var. PDEs), 2020
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10 Jun 2020
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