Translating novel insights from computational neuroscience into neuromorphic computing, we show how tightly balanced Spiking Neural Networks outperform existing networks in efficiency, robustness while maintaining competitive accuracy.
NoisyDECOLLE is a Python framework for assessing the robustness of SNNs trained with local learning rules inspired by three-factor learning and synaptic plasticity.