Empirical Study of the Topology and Geometry of Deep Networks

CVPR 2018 Alhussein FawziSeyed-Mohsen Moosavi-DezfooliPascal FrossardStefano Soatto

The goal of this paper is to analyze the geometric properties of deep neural network image classifiers in the input space. We specifically study the topology of classification regions created by deep networks, as well as their associated decision boundary... (read more)

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