Graph Convolutional Neural Networks

Watch SEI researcher Mr. Oren Wright discuss using graph signal processing formalisms to create new deep learning tools for graph convolutional neural networks (GCNNs) to answer the question "how does AI learn structure?" 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.