Spectral Graph Wavelet Transform as Feature Extractor for Machine Learning in Neuroimaging

Graph Signal Processing has become a very useful framework for signal operations and representations defined on irregular domains. Exploiting transformations that are defined on graph models can be highly beneficial when the graph encodes relationships between signals.