Forecasting Unobserved Node States with spatio-temporal Graph Neural Networks.
Andreas RothThomas LiebigPublished in: CoRR (2022)
Keyphrases
- spatio temporal
- neural network
- graph structure
- directed graph
- short term
- undirected graph
- backpropagation neural networks
- spatial and temporal
- betweenness centrality
- graph representation
- nodes of a graph
- pattern recognition
- edge weights
- random walk
- fuzzy logic
- finding the shortest path
- image sequences
- genetic algorithm
- graph model
- weighted graph
- graph theory
- fault diagnosis
- moving objects
- bipartite graph
- graph matching
- overlapping communities
- artificial neural networks
- path length
- directed acyclic graph
- graph mining
- connected components
- graph databases
- back propagation
- long term
- feed forward
- self organizing maps
- action recognition
- strongly connected
- partially observed
- neural nets