Elastic Weight Consolidation (EWC) engine calculating Fisher Information Matrix diagonal penalties to mitigate catastrophic forgetting in continual learning.
Read more at GenPark and the GenPark MCP Catalog.
graph TD
A[Task A Loss Minimization] --> B[Task A Optimal Weights theta_A*]
B --> C[Compute Fisher Diagonal F_i]
C --> D[Task B Training]
D --> E[L_total = L_B + (lambda/2) * sum F_i * (theta - theta_A*)^2]
E --> F[High Performance on Both Task A and Task B]
- Diagonal Fisher Information Matrix (FIM) estimation.
- Quadratic elasticity penalty and analytical gradient calculation.
- Pure Python 3.9+ standard library.