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cs.NE2024
Accurate Mapping of RNNs on Neuromorphic Hardware with Adaptive Spiking Neurons
Gauthier Boeshertz, Giacomo Indiveri, Manu Nair +1
Thanks to their parallel and sparse activity features, recurrent neural networks (RNNs) are well-suited for hardware implementation in low-power neuromorphic hardware. However, map…
cs.NE2024
Distributed Representations Enable Robust Multi-Timescale Symbolic Computation in Neuromorphic Hardware
Madison Cotteret, Hugh Greatorex, Alpha Renner +6
Programming recurrent spiking neural networks (RSNNs) to robustly perform multi-timescale computation remains a difficult challenge. To address this, we describe a single-shot weig…