neuromorphic-hardware

This paper proposes using intrinsic device noise on analog neuromorphic hardware as a resource for continual learning by conditioning each weight's stochastic dynamics to avoid crossing memory-critical barriers, demonstrating non-monotonic retention improvement and validation on BrainScaleS-2 silicon.