2026
Capacity-Agnostic Parameter Isolation for Continual Graph Learning
ICML 2026poster
Existing parameter isolation-based methods in continual learning employ diverse designs to learn more tasks within a limited model capacity. However, most of their designs inevitably incur substantial computational overhead if their model capacity is enlarged to accommodate further tasks as the task…