2 papers
cs.LG2026
Exploring napping paradigm for Recurrent Spiking Neural Networks
Andreas Massey, Stefano Nichele, Aliaksandr Hubin
Biological organisms minimize free energy by balancing two competing demands on their internal world model: it must be accurate enough to predict sensory input, yet simple enough t…
cs.NE2026
Sleep-Based Homeostatic Regularization for Stabilizing Spike-Timing-Dependent Plasticity in Recurrent Spiking Neural Networks
Andreas Massey, Aliaksandr Hubin, Stefano Nichele +1
Spike-timing-dependent plasticity (STDP) provides a biologically-plausible learning mechanism for spiking neural networks (SNNs); however, Hebbian weight updates in architectures w…