Graph Convolutional Neural Networks

Video
Oren Wright discusses using graph signal processing formalisms to create new deep learning tools for graph convolutional neural networks (GCNNs).
Publisher

Software Engineering Institute

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Abstract

This project used graph signal processing formalisms to create new deep learning tools for graph convolutional neural networks (GCNNs). Our approach employed topology-adaptive graph convolutional networks, introduced in 2017 by researchers at Carnegie Mellon University.