论文标题
深度神经网络的表现
Expressivity of Deep Neural Networks
论文作者
论文摘要
在本综述论文中，我们全面概述了神经网络的各种近似结果。讨论了经典函数空间的近似率以及深度神经网络比浅层函数类别的益处。虽然现有结果的主体是用于一般前馈架构，但我们还描述了卷积，残留和经常性神经网络的近似结果。
In this review paper, we give a comprehensive overview of the large variety of approximation results for neural networks. Approximation rates for classical function spaces as well as benefits of deep neural networks over shallow ones for specifically structured function classes are discussed. While the mainbody of existing results is for general feedforward architectures, we also depict approximation results for convolutional, residual and recurrent neural networks.
