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Robust Hierarchical Graph Classification with Subgraph Attention
Towards this end, we propose a graph classification algorithm called SubGattPool which jointly learns the subgraph attention and employs two different types of hierarchical attention mechanisms to find the important nodes in a hierarchy and the importance of individual hierarchies in a graph.
Unsupervised Graph Representation by Periphery and Hierarchical Information Maximization
Invent of graph neural networks has improved the state-of-the-art for both node and the entire graph representation in a vector space.
Subgraph Attention for Node Classification and Hierarchical Graph Pooling
Along with attention over the subgraphs, our pooling architecture also uses attention to determine the important nodes within a level graph and attention to determine the important levels in the whole hierarchy.
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