4 papers
Minibatch Processing in Spiking Neural Networks
Daniel J. Saunders, Cooper Sigrist, Kenneth Chaney +2
Spiking neural networks (SNNs) are a promising candidate for biologically-inspired and energy efficient computation. However, their simulation is notoriously time consuming, and ma…
Lattice Map Spiking Neural Networks (LM-SNNs) for Clustering and Classifying Image Data
Hananel Hazan, Daniel J. Saunders, Darpan T. Sanghavi +2
Spiking neural networks (SNNs) with a lattice architecture are introduced in this work, combining several desirable properties of SNNs and self-organized maps (SOMs). Networks are…
Locally Connected Spiking Neural Networks for Unsupervised Feature Learning
Daniel J. Saunders, Devdhar Patel, Hananel Hazan +2
In recent years, Spiking Neural Networks (SNNs) have demonstrated great successes in completing various Machine Learning tasks. We introduce a method for learning image features by…
Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to ATARI games
Devdhar Patel, Hananel Hazan, Daniel J. Saunders +2
Deep Reinforcement Learning (RL) demonstrates excellent performance on tasks that can be solved by trained policy. It plays a dominant role among cutting-edge machine learning appr…