Forecasting Unobserved Node States with spatio-temporal Graph Neural Networks.
Andreas RothThomas LiebigPublished in: ICDM (Workshops) (2022)
Keyphrases
- spatio temporal
- neural network
- graph structure
- directed graph
- graph theory
- short term
- undirected graph
- pattern recognition
- root node
- random walk
- spatial and temporal
- image sequences
- back propagation
- structured data
- multilayer perceptron
- overlapping communities
- space time
- tree structure
- neural network model
- backpropagation neural networks
- moving objects
- neural nets
- spatio temporal data
- edge weights
- directed acyclic graph
- long term
- nodes of a graph
- connected components
- finding the shortest path
- artificial neural networks
- path length
- graph representation
- training process
- weighted graph
- fuzzy logic
- bipartite graph
- prediction model
- graph matching
- feed forward
- graph model
- spatio temporal databases
- recurrent neural networks
- fault diagnosis