Adversarial Training for Graph Neural Networks.
Lukas GoschSimon GeislerDaniel SturmBertrand CharpentierDaniel ZügnerStephan GünnemannPublished in: CoRR (2023)
Keyphrases
- neural network
- training algorithm
- training process
- feedforward neural networks
- pattern recognition
- neural network training
- backpropagation algorithm
- multi layer perceptron
- feed forward neural networks
- random walk
- training examples
- back propagation
- error back propagation
- graph representation
- bipartite graph
- graph structure
- training set
- online learning
- graph matching
- recurrent networks
- associative memory
- neural network model
- radial basis function network
- multi layer
- multi agent
- structured data
- graph mining
- graph model
- training phase
- graph partitioning
- neural network structure
- graph theoretic
- graph theory
- activation function
- weighted graph
- recurrent neural networks
- multilayer perceptron
- feed forward
- self organizing maps
- supervised learning
- fuzzy logic
- hidden markov models
- artificial neural networks
- training data