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Topology and Prediction Focused Research on Graph Convolutional Neural Networks
[article]
2018
arXiv
pre-print
Important advances have been made using convolutional neural network (CNN) approaches to solve complicated problems in areas that rely on grid structured data such as image processing and object classification. Recently, research on graph convolutional neural networks (GCNN) has increased dramatically as researchers try to replicate the success of CNN for graph structured data. Unfortunately, traditional CNN methods are not readily transferable to GCNN, given the irregularity and geometric
arXiv:1808.07769v1
fatcat:tgjs62zqonb2ni6rjwiq3uv3ny