918 citations · 2.5k across the 22 of their papers we have counts for
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Spiking Generative Adversarial Networks With a Neural Network Discriminator: Local Training, Bayesian Models, and Continual Meta-Learning
Bleema Rosenfeld, Osvaldo Simeone, Bipin Rajendran
Neuromorphic data carries information in spatio-temporal patterns encoded by spikes. Accordingly, a central problem in neuromorphic computing is training spiking neural networks (S…
ESSOP: Efficient and Scalable Stochastic Outer Product Architecture for Deep Learning
Vinay Joshi, Geethan Karunaratne, Manuel Le Gallo +5
Deep neural networks (DNNs) have surpassed human-level accuracy in a variety of cognitive tasks but at the cost of significant memory/time requirements in DNN training. This limits…
Learning First-to-Spike Policies for Neuromorphic Control Using Policy Gradients
Bleema Rosenfeld, Osvaldo Simeone, Bipin Rajendran
Artificial Neural Networks (ANNs) are currently being used as function approximators in many state-of-the-art Reinforcement Learning (RL) algorithms. Spiking Neural Networks (SNNs)…