3 papers
cs.NE2021
Spiking Neural Networks with Improved Inherent Recurrence Dynamics for Sequential Learning
Wachirawit Ponghiran, Kaushik Roy
Spiking neural networks (SNNs) with leaky integrate and fire (LIF) neurons, can be operated in an event-driven manner and have internal states to retain information over time, prov…
cs.LG2019
Reinforcement Learning with Low-Complexity Liquid State Machines
Wachirawit Ponghiran, Gopalakrishnan Srinivasan, Kaushik Roy
We propose reinforcement learning on simple networks consisting of random connections of spiking neurons (both recurrent and feed-forward) that can learn complex tasks with very li…
cs.NE2019
A Comprehensive Analysis on Adversarial Robustness of Spiking Neural Networks
Saima Sharmin, Priyadarshini Panda, Syed Shakib Sarwar +3
In this era of machine learning models, their functionality is being threatened by adversarial attacks. In the face of this struggle for making artificial neural networks robust, f…