Continual Graph Learning: A Survey

1. 1Implement experience replay to reuse past samples during training
2. 2Use generative replay to synthesize informative subgraphs for rehearsal and address information loss and privacy risks
3. 3Evaluate the effectiveness of different Continual Graph Learning approaches on streaming graph-structured data

Data scientists and AI engineers working on graph-based models can benefit from Continual Graph Learning to improve model performance and adapt to changing data streams

💡 Continual Graph Learning enables incremental learning from streaming graph-structured data without forgetting previous knowledge

💡 Continual Graph Learning for streaming graph data