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An Introduction to Probabilistic Spiking Neural Networks: Probabilistic Models, Learning Rules, and Applications
Hyeryung Jang, Osvaldo Simeone, Brian Gardner +1
Spiking neural networks (SNNs) are distributed trainable systems whose computing elements, or neurons, are characterized by internal analog dynamics and by digital and sparse synap…
Federated Neuromorphic Learning of Spiking Neural Networks for Low-Power Edge Intelligence
Nicolas Skatchkovsky, Hyeryung Jang, Osvaldo Simeone
Spiking Neural Networks (SNNs) offer a promising alternative to conventional Artificial Neural Networks (ANNs) for the implementation of on-device low-power online learning and inf…
Optimizing Pipelined Computation and Communication for Latency-Constrained Edge Learning
Nicolas Skatchkovsky, Osvaldo Simeone
Consider a device that is connected to an edge processor via a communication channel. The device holds local data that is to be offloaded to the edge processor so as to train a mac…