Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification.
Moshe EliasofEldad HaberEran TreisterPublished in: CoRR (2022)
Keyphrases
- neural network
- graph structure
- directed graph
- pattern recognition
- training process
- training set
- multi layer perceptron
- training phase
- pattern classification
- tree structure
- training samples
- classification accuracy
- supervised learning
- decision trees
- text classification
- training patterns
- classification performances
- support vector machine svm
- finding the shortest path
- feature space
- rule extraction
- betweenness centrality
- feature extraction
- undirected graph
- backpropagation algorithm
- leaf nodes
- nodes of a graph
- directed acyclic graph
- bipartite graph
- class labels
- random walk
- image classification
- fuzzy logic
- support vector machine
- artificial neural networks
- genetic algorithm