Spectral Networks and Locally Connected Networks on Graphs
Abstract
Convolutional Neural Networks are extremely efficient architectures in image and audio recognition tasks, thanks to their ability to exploit the local translational invariance of signal classes over their domain. In this paper we consider possible generalizations of CNNs to signals defined on more general domains without the action of a translation group. In particular, we propose two constructions, one based upon a hierarchical clustering of...
Paper Details
Title
Spectral Networks and Locally Connected Networks on Graphs
Published Date
Dec 21, 2013
Journal
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