On Explainability of Graph Neural Networks via Subgraph Explorations.
Hao YuanHaiyang YuJie WangKang LiShuiwang JiPublished in: ICML (2021)
Keyphrases
- neural network
- graph mining
- graph databases
- graph data
- graph properties
- subgraph isomorphism
- graph classification
- labeled graphs
- bipartite graph
- maximum weight
- maximum matching
- pattern recognition
- frequent subgraph mining
- subgraph mining
- back propagation
- frequent subgraphs
- graph search
- edge weights
- graph theory
- graph matching
- structured data
- connected subgraphs
- graph model
- artificial neural networks
- graph representation
- similarity graph
- dense subgraphs
- subgraph matching
- genetic algorithm
- graph theoretic
- graph partitioning
- fault diagnosis
- graph structure
- neural network model
- fuzzy logic
- directed acyclic graph
- neural nets
- recurrent neural networks
- query graph
- stable set
- multilayer perceptron
- directed graph
- search space
- random walk
- pattern mining
- maximum clique
- multi layer
- spanning tree
- minimum spanning tree
- biological networks