A Gentle Introduction to Graph Neural Networks by Benjamin Sanchez-Langeling, Emily Reif, Adam Pearce, Alexander B. Wiltschko
This document provides an introduction to graph neural networks (GNNs) and explores the components needed for building a GNN. It discusses the applications of GNNs in various fields and explains the different types of attributes in a graph. The document also showcases how images and text can be represented as graphs and provides examples to illustrate the concepts. See the original at https//distill.pub/2021/gnn-intro/.
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