A flexible generative framework for graph-based semi-supervised learning

Keyphrases

• Bayesian Probability 33%
• Benchmark Dataset 33%
• Family of Distributions 33%
• Generative Framework 100%
• Graph Network 33%
• Graph Neural Network 33%
• Graph Regularization 33%
• Graph Structure 66%
• Graph-based Semi-supervised Learning 100%
• Inference Methods 33%
• Joint Distribution 66%
• Labeled Sample 33%
• Learning Task 33%
• Missing Labels 33%
• Network Science 33%
• Network Structure 33%
• Node Features 33%
• Random Graph Models 33%
• Recent Advances 33%
• Regularization Method 33%
• Relational Information 33%
• Sampling Methods 33%
• Science Literature 33%
• Semi-supervised Learning 33%
• State-of-the-art Models 33%
• Unlabeled Graphs 33%
• Variational Inference 33%

Computer Science

• Graph Neural Network 25%
• Inference Technique 25%
• Joint Distribution 50%
• Network Science 25%
• Network Structures 25%
• Random Graphs 25%
• Regularization Method 25%
• Semisupervised Learning 100%
• Small Proportion 25%
• Structured Data 25%