论文标题
Relu神经网络的本地线性属性
Locally Linear Attributes of ReLU Neural Networks
论文作者
论文摘要
Relu神经网络确定/是从输入空间到输出空间的连续分段线性图。神经网络中的权重决定了输入空间分解为凸多型的分解，并且在这些杂货中的每一个都可以通过单个仿射映射来描述网络。可以分析分解的结构，以及附着在每个多层的仿射图，以研究相关神经网络的行为。
A ReLU neural network determines/is a continuous piecewise linear map from an input space to an output space. The weights in the neural network determine a decomposition of the input space into convex polytopes and on each of these polytopes the network can be described by a single affine mapping. The structure of the decomposition, together with the affine map attached to each polytope, can be analyzed to investigate the behavior of the associated neural network.
