5 citations · 8 across the 4 of their papers we have counts for
7 papers
Memory via Temporal Delays in weightless Spiking Neural Network
Hananel Hazan, Simon Caby, Christopher Earl +2
A common view in the neuroscience community is that memory is encoded in the connection strength between neurons. This perception led artificial neural network models to focus on c…
Reinforcement learning with a network of spiking agents
Sneha Aenugu, Abhishek Sharma, Sasikiran Yelamarthi +3
Neuroscientific theory suggests that dopaminergic neurons broadcast global reward prediction errors to large areas of the brain influencing the synaptic plasticity of the neurons i…
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…
Unsupervised Learning with Self-Organizing Spiking Neural Networks
Hananel Hazan, Daniel J. Saunders, Darpan T. Sanghavi +2
We present a system comprising a hybridization of self-organized map (SOM) properties with spiking neural networks (SNNs) that retain many of the features of SOMs. Networks are tra…