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Survey of Deep Learning on Graphs by Às Mã is a document available to read on EtoBox.

What is Survey of Deep Learning on Graphs about?

This document surveys deep learning methods that have been applied to graph data. It divides existing graph deep learning methods into five categories: graph recurrent neural networks, graph convolutional networks, graph autoencoders, graph reinforcement learning, and graph adversarial methods. The document provides an overview of each category and analyzes their differences. It discusses challenges in applying deep learning to graph data, such as irregular graph structures and heterogeneous graph propertie

Author

Às Mã

Language

EN