Search Results for author:
Found 3 papers, 0 papers with code
Explicitly Trained Spiking Sparsity in Spiking Neural Networks with Backpropagation
Spiking Neural Networks (SNNs) are being explored for their potential energy efficiency resulting from sparse, event-driven computations.
Controlled Forgetting: Targeted Stimulation and Dopaminergic Plasticity Modulation for Unsupervised Lifelong Learning in Spiking Neural Networks
Stochastic gradient descent requires that training samples be drawn from a uniformly random distribution of the data.
ASP: Learning to Forget with Adaptive Synaptic Plasticity in Spiking Neural Networks
Against this backdrop, we present a novel unsupervised learning mechanism ASP (Adaptive Synaptic Plasticity) for improved recognition with Spiking Neural Networks (SNNs) for real time on-line learning in a dynamic environment.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
