Geometric wavelet scattering on graphs and manifolds
Published: Sep 9, 2019
Abstract
Convolutional neural networks (CNNs) are revolutionizing imaging science for two- and three-dimensional images over Euclidean domains. However, many data sets are intrinsically non-Euclidean and are better modeled through other mathematical structures, such as graphs or manifolds. This state of affairs has led to the development of geometric deep learning, which refers to a body of research that aims to translate the principles of CNNs to these...
Paper Details
Title
Geometric wavelet scattering on graphs and manifolds
Published Date
Sep 9, 2019
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