Simple reference implementation of GraphSAGE.
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Updated
Mar 23, 2018 - Python
Simple reference implementation of GraphSAGE.
This is the PyTorch-0.4.0 implementation of few-shot learning on CIFAR-100 with graph neural networks (GNN)
A simple Pytorch implementation of Gated Graph Neural Networks
graph network and knowledge graph models
Keras implementation of the graph attention networks (GAT) by Veličković et al. (2017; https://arxiv.org/abs/1710.10903)
A convenient wrapper to develop graph neural networks with Keras. Currently under development with the objective of integrating Networkx, Owlready2 and oneM2M for cognitive IoT.
state-lstm in pytorch
Reproduction work of "Neural Relational Inference for Interacting Systems" in Chainer
A list of interesting graph neural networks (GNN) links with a primary interest in recommendations and tensorflow that is continually updated and refined
Classification Task on Graphs using Graph Neural Networks and Graph Kernels - Thesis Project
MAGNet: Multi-agents control using Graph Neural Networks
Open source machine learning for graph-structured data
Re-implementation and extension of the work described in "Learning to Represent Programs with Graphs"
MATH 490 Final Project: Approximating solutions to the decision variant of the TSP with Graph Neural Networks
This is a tutorial for PyTorch Geometric on the YooChoose dataset
Representation Learning on Graphs with Jumping Knowledge Networks
Pytorch Implementation of GNN Meta Attack paper.
learning GNNs
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