Quantization-aware training with a frozen state matrix lifts sequential MNIST accuracy from 40% under post-training quantization to 96%, and a heterogeneous precision scheme cuts memory by 6 times.
Scalable event-by-event processing of neuromorphic sensory signals with deep state-space models,
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Quantizing Small-Scale State-Space Models for Edge AI
Quantization-aware training with a frozen state matrix lifts sequential MNIST accuracy from 40% under post-training quantization to 96%, and a heterogeneous precision scheme cuts memory by 6 times.