Stochastic Engrams for Efficient Continual Learning
The engramBNN method addresses catastrophic forgetting in neural networks by integrating stochastic, memory-inspired 'engrams' into a metaplastic binarized network. This novel approach uses these engrams as a dynamic gating mechanism to selectively retain relevant knowledge, achieving high accuracy on incremental learning tasks while significantly reducing GPU and RAM usage.