Can We Understand Plasticity Through Neural Collapse?

Understand

This paper explores the connection between two recently identified phenomena in deep learning: plasticity loss and neural collapse.

• We analyze their correlation in different scenarios, revealing a significant association during the initial training phase on the first task.
• Additionally, we introduce a regularization approach to mitigate neural collapse, demonstrating its effectiveness in alleviating plasticity loss in this specific setting.