Efficient Graph Generation with Graph Recurrent Attention Networks
Liao et al.: https://arxiv.org/abs/1910.00760
Code: https://github.com/lrjconan/GRAN
#Graph #MachineLearning #NeuralNetworks
Liao et al.: https://arxiv.org/abs/1910.00760
Code: https://github.com/lrjconan/GRAN
#Graph #MachineLearning #NeuralNetworks
arXiv.org
Efficient Graph Generation with Graph Recurrent Attention Networks
We propose a new family of efficient and expressive deep generative models of graphs, called Graph Recurrent Attention Networks (GRANs). Our model generates graphs one block of nodes and...
GNNExplainer: Generating Explanations for Graph Neural Networks
Ying et al. : https://arxiv.org/abs/1903.03894
Code : https://github.com/RexYing/gnn-model-explainer
#ArtificialIntelligence #Graph #NeuralNetworks
Ying et al. : https://arxiv.org/abs/1903.03894
Code : https://github.com/RexYing/gnn-model-explainer
#ArtificialIntelligence #Graph #NeuralNetworks
GitHub
GitHub - RexYing/gnn-model-explainer: gnn explainer
gnn explainer. Contribute to RexYing/gnn-model-explainer development by creating an account on GitHub.
Hierarchical Graph Pooling with Structure Learning
Zhang et al.: https://arxiv.org/abs/1911.05954
#ArtificialIntelligence #Graph #NeuralNetworks
Zhang et al.: https://arxiv.org/abs/1911.05954
#ArtificialIntelligence #Graph #NeuralNetworks
arXiv.org
Hierarchical Graph Pooling with Structure Learning
Graph Neural Networks (GNNs), which generalize deep neural networks to graph-structured data, have drawn considerable attention and achieved state-of-the-art performance in numerous graph related...
Efficient Graph Generation with Graph Recurrent Attention Networks
Liao et al.: https://arxiv.org/abs/1910.00760
Code: https://github.com/lrjconan/GRAN
#Graph #NeuralNetworks #NeurIPS #NeurIPS2019
Liao et al.: https://arxiv.org/abs/1910.00760
Code: https://github.com/lrjconan/GRAN
#Graph #NeuralNetworks #NeurIPS #NeurIPS2019
GitHub
GitHub - lrjconan/GRAN: Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph…
Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph Neural Networks, NeurIPS 2019 - lrjconan/GRAN
Exploring the London Stock Exchange using Graph Networks in Neo4j — Part 1
A PRACTICAL GUIDE, USING GRAPH DATABASES, PYTHON AND DOCKER
Daniel Sharp: https://medium.com/applied-data-science/exploring-stocks-in-the-london-stock-exchange-using-graph-networks-in-neo4j-part-1-58a5455084ab
#Graph #Database #Python #Docker
A PRACTICAL GUIDE, USING GRAPH DATABASES, PYTHON AND DOCKER
Daniel Sharp: https://medium.com/applied-data-science/exploring-stocks-in-the-london-stock-exchange-using-graph-networks-in-neo4j-part-1-58a5455084ab
#Graph #Database #Python #Docker
Medium
Exploring the London Stock Exchange using Graph Networks in Neo4j — Part 1
Back in December I attended an event called ‘Network Science in Financial Service’ at the Alan Turing Institute. I found the approach of…
Deep learning with graph-structured representations
T.N. Kipf : https://dare.uva.nl/search?identifier=1b63b965-24c4-4bcd-aabb-b849056fa76d
#DeepLearning #Graph #NeuralNetworks
T.N. Kipf : https://dare.uva.nl/search?identifier=1b63b965-24c4-4bcd-aabb-b849056fa76d
#DeepLearning #Graph #NeuralNetworks
dare.uva.nl
Digital Academic Repository - University of Amsterdam