457 citations · 547 across the 21 of their papers we have counts for
5 papers · 1 filter
NeuroTrain: Surveying Local Learning Rules for Spiking Neural Networks with an Open Benchmarking Framework
Alessio Caviglia, Filippo Marostica, Roberta Bardini +2
The rapid expansion of spiking neural networks (SNNs) has led to a proliferation of training algorithms that differ widely in biological inspiration, computational structure, and h…
Elastic Spiking Transformers for Efficient Gesture Understanding
Alberto Ancilotto, Gianluca Amprimo, Stefano Di Carlo +1
Spiking Neural Networks (SNNs), particularly Spiking Transformers, offer energy-efficient processing of event-based sensor data for healthcare applications. Yet current architectur…
Compressed Latent Replays for Lightweight Continual Learning on Spiking Neural Networks
Alberto Dequino, Alessio Carpegna, Davide Nadalini +4
Rehearsal-based Continual Learning (CL) has been intensely investigated in Deep Neural Networks (DNNs). However, its application in Spiking Neural Networks (SNNs) has not been expl…
SpikeExplorer: hardware-oriented Design Space Exploration for Spiking Neural Networks on FPGA
Dario Padovano, Alessio Carpegna, Alessandro Savino +1
One of today's main concerns is to bring Artificial Intelligence power to embedded systems for edge applications. The hardware resources and power consumption required by state-of-…
Spiker+: a framework for the generation of efficient Spiking Neural Networks FPGA accelerators for inference at the edge
Alessio Carpegna, Alessandro Savino, Stefano Di Carlo
Including Artificial Neural Networks in embedded systems at the edge allows applications to exploit Artificial Intelligence capabilities directly within devices operating at the ne…