What Matters in Graph Class Incremental Learning An Information Preservation Perspective
–Neural Information Processing Systems
Graph class incremental learning (GCIL) requires the model to classify emerging nodes of new classes while remembering old classes. Existing methods are designed to preserve effective information of old models or graph data to alleviate forgetting, but there is no clear theoretical understanding of what matters in information preservation.
Neural Information Processing Systems
Oct-9-2025, 22:13:08 GMT
- Country:
- Asia > China
- Hong Kong (0.04)
- Tianjin Province > Tianjin (0.04)
- Asia > China
- Genre:
- Research Report > Experimental Study (0.93)
- Industry:
- Information Technology (0.92)
- Technology: