Stochastic Blockmodels meet Graph Neural Networks.
Nikhil MehtaLawrence CarinPiyush RaiPublished in: ICML (2019)
Keyphrases
- neural network
- dynamic graph
- pattern recognition
- random walk
- back propagation
- graph representation
- structured data
- graph structure
- graph theoretic
- feed forward
- graph theory
- recurrent neural networks
- multilayer perceptron
- graph databases
- graph mining
- stochastic model
- graph structures
- bipartite graph
- graph matching
- directed graph
- self organizing maps
- fuzzy logic
- genetic algorithm
- weighted graph
- multi layer
- connected components
- monte carlo
- markov random field
- learning automata
- artificial neural networks
- maximum flow