GFCN: A New Graph Convolutional Network Based on Parallel Flows.
Feng JiJielong YangQiang ZhangWee Peng TayPublished in: ICASSP (2020)
Keyphrases
- connected components
- graph theory
- depth first search
- graph representation
- bipartite graph
- graph structure
- weighted graph
- parallel implementation
- graph databases
- parallel programming
- graph mining
- graph theoretic
- massively parallel
- parallel computing
- directed acyclic graph
- parallel processing
- random walk
- clustering algorithm
- graph structures
- stable set
- machine learning
- deep learning
- random graphs
- shared memory
- graph model
- directed graph