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.
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Updated
Dec 28, 2018 - Python
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.
learning GNNs
resources for graph convolutional networks (图卷积神经网络相关资源)
Some introductory material for GraphNN wrapped together
A deep learning library for graph data structures
Heterogeneous Graph Attention Networks for Early Detection of Rumors on Twitter (IJCNN 2020)
DeepInf: Social Influence Prediction with Deep Learning
Graph-neural-network
KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019
Text Classification using Graph Convolutional Neural Networks and Natural Language Processing Techniques
PyTorch implementation of the paper "Graph Attention Networks". (ICLR 2018)
A TensorFlow 2 implementation of Graph Attention Networks (GAT)
Code for the paper "NABU - Multilingual Graph-based Neural RDF Verbalizer"
Implementation of CAGNIR, a new Neural Information Retrieval model aggregates relevant semantics through applying Graph Attention Networks on the Click Graph.
Bi-Level Graph Neural Networks for Drug-Drug Interaction Prediction. ICML 2020 Graph Representation Learning and Beyond (GRL+) Workshop
Graph Neural networks for NLP
Keras implementation of the graph attention networks (GAT) by Veličković et al. (2017; https://arxiv.org/abs/1710.10903)
Implementation of CoulGAT framework and screened Coulomb attention mechanism.
[NIPS 2020] Graph Geometry Interaction Learning
Pytorch code for estimating the presence of the West Nile Disease employing Graph Neural network
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