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Understanding the Basis of Graph Convolutional Neural Networks via an Intuitive Matched Filtering Approach [Lecture Notes]

Ljubiša Stanković, Danilo P. Mandic

2023IEEE Signal Processing Magazine16 citationsDOI

Abstract

Graph convolutional neural networks (GCNNs) are becoming a model of choice for learning on irregular domains. However, due to the black-box nature of NNs, their underlying principles are rarely examined in depth.

Topics & Concepts

Computer scienceConvolutional neural networkGraphArtificial intelligenceBasis (linear algebra)Theoretical computer scienceMachine learningMathematicsGeometryAdvanced Graph Neural NetworksMultimodal Machine Learning ApplicationsGraph Theory and Algorithms
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