8 citations · 12 across the 12 of their papers we have counts for
Showing 2023 · cs.NEShow all
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cs.NE2023★ 1 cited
Agreeing to Stop: Reliable Latency-Adaptive Decision Making via Ensembles of Spiking Neural Networks
Jiechen Chen, Sangwoo Park, Osvaldo Simeone
Spiking neural networks (SNNs) are recurrent models that can leverage sparsity in input time series to efficiently carry out tasks such as classification. Additional efficiency gai…
cs.NE2023★ 1 cited
Knowing When to Stop: Delay-Adaptive Spiking Neural Network Classifiers with Reliability Guarantees
Jiechen Chen, Sangwoo Park, Osvaldo Simeone
Spiking neural networks (SNNs) process time-series data via internal event-driven neural dynamics. The energy consumption of an SNN depends on the number of spikes exchanged betwee…