SLGCN: Structure Learning Graph Convolutional Networks for Graphs under Heterophily.
Mengying JiangGuizhong LiuYuanchao SuXinliang WuPublished in: CoRR (2021)
Keyphrases
- structure learning
- graph structure
- graphical models
- graph structures
- network structure
- small world
- graph layout
- edge weights
- graph theory
- directed graph
- bayesian networks
- weighted graph
- graph theoretic
- conditional independence
- parameter learning
- complex networks
- gene regulatory networks
- densely connected
- structural learning
- graph mining
- social networks
- undirected graph
- spanning tree
- markov networks
- directed acyclic graph
- random variables
- parameter estimation
- probabilistic model
- markov logic networks
- belief propagation
- transfer learning
- probabilistic graphical models
- sample size
- random walk
- upper bound
- active learning
- training set