A toolkit for mapping networks of political and economic influence through diverse types of entities and their relations. Accessible at http://granoproject.org
A list of interesting graph neural networks (GNN) links with a primary interest in recommendations and tensorflow that is continually updated and refined
Explainability techniques for Graph Networks, applied to a synthetic dataset and an organic chemistry task. Code for the workshop paper "Explainability Techniques for Graph Convolutional Networks" (ICML19)
Implements a disparity filter in Python, based on graphs in NetworkX, to extract the multiscale backbone of a complex weighted network (Serrano, et al., 2009)
The code for the NeurIPS 2019 Graph Representation Learning workshop paper "Learning Visual Dynamics Models of Rigid Objects using Relational Inductive Biases" (Ferreira et al., 2019)