3 papers
cs.LG2026
Practical Bayesian Inference for Speech SNNs: Uncertainty and Loss-Landscape Smoothing
Yesmine Abdennadher, Philip N. Garner
Spiking Neural Networks (SNNs) are naturally suited for speech processing tasks due to their specific dynamics, which allows them to handle temporal data. However, the threshold-ba…
cs.LG2025
Convolutional Spiking-based GRU Cell for Spatio-temporal Data
Yesmine Abdennadher, Eleonora Cicciarella, Michele Rossi
Spike-based temporal messaging enables SNNs to efficiently process both purely temporal and spatio-temporal time-series or event-driven data. Combining SNNs with Gated Recurrent Un…
cs.NE2025
LightSNN: Lightweight Architecture Search for Sparse and Accurate Spiking Neural Networks
Yesmine Abdennadher, Giovanni Perin, Riccardo Mazzieri +2
Spiking Neural Networks (SNNs) are highly regarded for their energy efficiency, inherent activation sparsity, and suitability for real-time processing in edge devices. However, mos…