De Bruijn Goes Neural: Causality-Aware Graph Neural Networks for Time Series Data on Dynamic Graphs.
Lisi QarkaxhijaVincenzo PerriIngo ScholtesPublished in: LoG (2022)
Keyphrases
- neural network
- graph structure
- dynamic graph
- graph theory
- dynamic networks
- directed graph
- graph matching
- network architecture
- graph representation
- graph structures
- graph classification
- graph theoretical
- weighted graph
- graph theoretic
- graph representations
- graph databases
- graph model
- graph clustering
- pattern recognition
- graph properties
- bipartite graph
- graph mining
- graphical models
- series parallel
- random walk
- graph data
- neural fuzzy
- neural network model
- random graphs
- structural pattern recognition
- graph construction
- graph search
- graph kernels
- spanning tree
- structured data
- adjacency matrix
- artificial neural networks
- labeled graphs
- minimum spanning tree
- associative memory
- graph partitioning
- graph patterns
- maximum clique
- finding the shortest path
- directed acyclic
- undirected graph
- real world graphs
- graph isomorphism
- surprising patterns
- connectionist models
- neural model
- small world
- causal models
- pattern discovery
- connected components
- network structure