Iteration over event space in time-to-first-spike spiking neural networks for Twitter bot classification - Pabian, Mateusz; Rzepka, Dominik; Pawlak, Mirosław (Zielona Góra: Uniwersytet Zielonogórski)
This study proposes a variant of a time-coding time-to-first-spike spiking neural network (SNN) model with its neurons capable of generating spike trains in response to observed event sequences. This extends an existing model that is limited to generating and observing at most one event per synapse. We explain spike propagation through a model with multiple input and output spikes at each neuron, as well as design training rules for end-to-end backpropagation for event sequence data.
Keywords: spiking neural networks; event-based computing; bot detection; supervised learning