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High-order approximation rates for shallow neural networks with cosine and ReLU activation functions

Jonathan W. Siegel, Jinchao Xu

2021Applied and Computational Harmonic Analysis43 citationsDOI

Topics & Concepts

MathematicsSmoothnessDimension (graph theory)Activation functionArtificial neural networkFunction (biology)Mathematical analysisTrigonometric functionsPolynomialFunction approximationApplied mathematicsCombinatoricsGeometryComputer scienceBiologyMachine learningEvolutionary biologyNeural Networks and ApplicationsMachine Learning and ELMMachine Learning in Materials Science
High-order approximation rates for shallow neural networks with cosine and ReLU activation functions | Litcius