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Graph Convolutional Neural Networks (GCNN) Collection

These publications describe the SEI’s applied graph signal processing techniques that create new tools for GCNNs.

Publisher:

Software Engineering Institute

Abstract

Large, complex datasets (e.g., sensor data, web traffic) require new approaches to graph processing. The SEI applied graph signal processing techniques to create new tools for graph convolutional neural networks (GCNNs), extending deep learning to graph problems.

Collection Contents