GitHub

Graph Convolutional Networks

This is a TensorFlow implementation of Graph Convolutional Networks for the task of (semi-supervised) classification of nodes in a graph, as described in our paper: Thomas N. Kipf, Max Welling, ...
The New York Times

What's Going On in This Graph?

Who are the adults in children’s lives? By The Learning Network Will you have a white Christmas this year? What do you notice about the map below? What questions does it raise for you? By The Learning ...
IEEE

A new model for learning in graph domains

Abstract: In several applications the information is naturally represented by graphs. Traditional approaches cope with graphical data structures using a preprocessing phase which transforms the graphs ...
IEEE

Semi-Supervised Learning With Graph Learning-Convolutional Networks

Abstract: Graph Convolutional Neural Networks (graph CNNs) have been widely used for graph data representation and semi-supervised learning tasks. However, existing graph CNNs generally use a fixed ...
GitHub

GraphSage: Representation Learning on Large Graphs

This directory contains code necessary to run the GraphSage algorithm. GraphSage can be viewed as a stochastic generalization of graph convolutions, and it is especially useful for massive, dynamic ...