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Found 3 papers, 1 papers with code
Probabilistic Metaplasticity for Continual Learning with Memristors
The proposed mechanism eliminates high-precision modification to weight magnitude and consequently, high-precision memory for gradient accumulation.
NeuroBench: A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems
The NeuroBench framework introduces a common set of tools and systematic methodology for inclusive benchmark measurement, delivering an objective reference framework for quantifying neuromorphic approaches in both hardware-independent (algorithm track) and hardware-dependent (system track) settings.
TENT: Efficient Quantization of Neural Networks on the tiny Edge with Tapered FixEd PoiNT
In this research, we propose a new low-precision framework, TENT, to leverage the benefits of a tapered fixed-point numerical format in TinyML models.
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