QuanGCN: Noise-Adaptive Training for Robust Quantum Graph Convolutional Networks.
Kaixiong ZhouZhenyu ZhangShengyuan ChenTianlong ChenXiao HuangZhangyang WangXia HuPublished in: CoRR (2022)
Keyphrases
- image noise
- noisy environments
- average degree
- graph representation
- network structure
- directed graph
- salt pepper
- random walk
- missing data
- recurrent networks
- social networks
- geometric distortions
- graph databases
- greater robustness
- degree distribution
- directed acyclic graph
- graph structure
- bipartite graph
- edge detection
- training set