Boosting the Cycle Counting Power of Graph Neural Networks with I$^2$-GNNs.
Yinan HuangXingang PengJianzhu MaMuhan ZhangPublished in: ICLR (2023)
Keyphrases
- neural network
- graph theory
- pattern recognition
- power consumption
- graph structure
- structured data
- fuzzy logic
- directed graph
- genetic algorithm
- weighted graph
- bipartite graph
- recurrent neural networks
- graph representation
- connected components
- artificial neural networks
- learning algorithm
- self organizing maps
- graph matching
- graph theoretic
- decision trees
- graph model
- multi layer
- graph databases
- noise tolerant
- ensemble learning
- ensemble methods
- feed forward
- random walk
- bayesian networks