440 citations · 622 across the 13 of their papers we have counts for
6 papers · 1 filter
RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network
Bing Han, Gopalakrishnan Srinivasan, Kaushik Roy
Spiking Neural Networks (SNNs) have recently attracted significant research interest as the third generation of artificial neural networks that can enable low-power event-driven da…
Explicitly Trained Spiking Sparsity in Spiking Neural Networks with Backpropagation
Jason M. Allred, Steven J. Spencer, Gopalakrishnan Srinivasan +1
Spiking Neural Networks (SNNs) are being explored for their potential energy efficiency resulting from sparse, event-driven computations. Many recent works have demonstrated effect…
Enabling Spike-based Backpropagation for Training Deep Neural Network Architectures
Chankyu Lee, Syed Shakib Sarwar, Priyadarshini Panda +2
Spiking Neural Networks (SNNs) have recently emerged as a prominent neural computing paradigm. However, the typical shallow SNN architectures have limited capacity for expressing c…
Convolutional Spike Timing Dependent Plasticity based Feature Learning in Spiking Neural Networks
Priyadarshini Panda, Gopalakrishnan Srinivasan, Kaushik Roy
Brain-inspired learning models attempt to mimic the cortical architecture and computations performed in the neurons and synapses constituting the human brain to achieve its efficie…
Proposal for a Leaky-Integrate-Fire Spiking Neuron based on Magneto-Electric Switching of Ferro-magnets
Akhilesh Jaiswal, Sourjya Roy, Gopalakrishnan Srinivasan +1
The efficiency of the human brain in performing classification tasks has attracted considerable research interest in brain-inspired neuromorphic computing. Hardware implementations…
Significance Driven Hybrid 8T-6T SRAM for Energy-Efficient Synaptic Storage in Artificial Neural Networks
Gopalakrishnan Srinivasan, Parami Wijesinghe, Syed Shakib Sarwar +2
Multilayered artificial neural networks (ANN) have found widespread utility in classification and recognition applications. The scale and complexity of such networks together with…