Towards explaining graph neural networks via preserving prediction ranking and structural dependency.
Youmin ZhangWilliam K. CheungQun LiuGuoyin WangLili YangLi LiuPublished in: Inf. Process. Manag. (2024)
Keyphrases
- neural network
- prediction accuracy
- link analysis
- prediction model
- ranking algorithm
- artificial neural networks to predict
- dependency graph
- graph representation
- neural network ensemble
- learning to rank
- pattern recognition
- fuzzy logic
- random walk
- ordinal regression
- structural information
- ranking functions
- multi layer perceptron
- graph theoretic
- mutual reinforcement
- connected components
- graph model
- artificial neural networks
- bipartite graph
- weighted graph
- prediction algorithm
- fault diagnosis
- directed acyclic graph
- neural nets
- neural networks and support vector machines
- feed forward
- neural network model
- tag recommendation
- structured data
- social networks
- spanning tree
- graph structure
- graph theory
- ranked list
- recurrent neural networks
- multilayer perceptron
- graph matching
- directed graph
- self organizing maps