Community detection with spiking neural networks for neuromorphic hardware

Abstract

We present results related to the performance of an algorithm for community detection which incorporates event-driven computation. We define a mapping which takes a graph 𝒢 to a system of symmetrically connected, spiking neurons and use spike train similarities to identify vertex communities. On a random graph with 128 vertices and known community… (More)
DOI: 10.1145/3183584.3183621

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