BayesGrad: Explaining Predictions of Graph Convolutional Networks.
Hirotaka AkitaKosuke NakagoTomoki KomatsuYohei SugawaraShin-ichi MaedaYukino BabaHisashi KashimaPublished in: CoRR (2018)
Keyphrases
- edge weights
- social networks
- highly connected
- average degree
- directed graph
- graph representation
- graph structure
- network design
- community discovery
- bipartite graph
- weighted graph
- heterogeneous networks
- network size
- graph clustering
- small world
- dynamic networks
- social graphs
- graph based algorithm
- overlapping communities
- densely connected
- graph model
- network model
- network analysis
- graph theory
- graph layout
- directed edges
- random walk
- betweenness centrality
- machine learning
- heterogeneous social networks
- degree distribution
- citation networks
- maximum flow
- fully connected
- deep learning
- network architecture
- graph matching
- unsupervised learning
- learning algorithm