Spiking neural networks (SNNs) process time-series data via internal event-driven neural dynamics whose energy consumption depends on the number of spikes exchanged between neurons over the course of the  ...  To address this problem, we introduce a novel delay-adaptive SNN-based inference methodology that, wrapping around any pre-trained SNN classifier, provides guaranteed reliability for the decisions produced  ...  Spiking Neural Network Model In this work, we adopt the standard LIF neural model known as spike response model (SRM) [34] . Consider a set of spiking neurons indexed via integers in set K.  ...