Mistake gating leads to energy and memory efficient continual learning

Implement an energy-efficient training layer that uses 'mistake gating' to skip backpropagation on correctly classified samples. This is vital for on-device incremental learning.

Suggested repo: gate-learn

"Reduce training energy consumption by 50% by teaching your model to ignore what it already knows."

Estimated effort: 45h