28 citations · 56 across the 11 of their papers we have counts for
4 papers · 1 filter
Efficient Uncertainty Estimation in Spiking Neural Networks via MC-dropout
Tao Sun, Bojian Yin, Sander Bohte
Spiking neural networks (SNNs) have gained attention as models of sparse and event-driven communication of biological neurons, and as such have shown increasing promise for energy-…
Accurate online training of dynamical spiking neural networks through Forward Propagation Through Time
Bojian Yin, Federico Corradi, Sander M. Bohte
The event-driven and sparse nature of communication between spiking neurons in the brain holds great promise for flexible and energy-efficient AI. Recent advances in learning algor…
Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks
Bojian Yin, Federico Corradi, Sander M. Bohte
Inspired by more detailed modeling of biological neurons, Spiking neural networks (SNNs) have been investigated both as more biologically plausible and potentially more powerful mo…
Effective and Efficient Computation with Multiple-timescale Spiking Recurrent Neural Networks
Bojian Yin, Federico Corradi, Sander M. Bohté
The emergence of brain-inspired neuromorphic computing as a paradigm for edge AI is motivating the search for high-performance and efficient spiking neural networks to run on this…