graph-networks

Build Graph Nets in Tensorflow

Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集

TypeDB-ML is the Machine Learning integrations library for TypeDB

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

A list of interesting graph neural networks (GNN) links with a primary interest in recommendations and tensorflow that is continually updated and refined

A toolkit for mapping networks of political and economic influence through diverse types of entities and their relations. Accessible at http://granoproject.org

[CVPR2019]Occlusion-Net: 2D/3D Occluded Keypoint Localization Using Graph Networks

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)

Graph convolution with tf.keras

Reimplementation of Learning Mesh-based Simulation With Graph Networks

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)

Graph Neural networks for NLP

Code for "Distributed, Egocentric Representations of Graphs for Detecting Critical Structures" (ICML 2019)

Graph Nets (GN) implement by pytorch

A PyTorch library for Graph Convolutional Networks.

Student research project on pagerank estimation with deep graph networks

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)

This code is implemented according to paper "Scalable and Parallel Deep Bayesian Optimization on Attributed Graphs", accepted by TNNLS. (Python2/TensorFlow)

Implementation of Relation Mask R-CNN with Graph Permutation Invariant Networks

graph network and knowledge graph models