Atom: Neural Traffic Compression with Spatio-Temporal Graph Neural Networks.
Paul AlmasanKrzysztof RusekShihan XiaoXiang ShiXiangle ChengAlbert Cabellos-AparicioPere Barlet-RosPublished in: CoRR (2023)
Keyphrases
- neural network
- spatio temporal
- network architecture
- movement patterns
- neural model
- real time
- artificial neural networks
- spatial and temporal
- neural learning
- graph theory
- random walk
- graph representation
- learning rules
- associative memory
- compression algorithm
- directed acyclic graph
- neural network model
- data compression
- bio inspired
- feed forward
- connectionist models
- pattern recognition
- neural fuzzy
- spanning tree
- bipartite graph
- traffic flow
- graph structure
- image sequences
- compression scheme
- genetic algorithm
- neural nets
- recurrent neural networks
- connected components
- back propagation
- neural computation
- fuzzy systems
- fuzzy logic
- recurrent networks
- spatio temporal data
- network traffic
- road network
- graph databases
- graph model