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20122021
most citedGabor Filter Assisted Energy Efficient Fast Learning Convolutional Neural Networks

79 citations · 495 across the 38 of their papers we have counts for

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17 papers · 1 filter

cs.NE20211 cited

Oscillatory Fourier Neural Network: A Compact and Efficient Architecture for Sequential Processing

Bing Han, Cheng Wang, Kaushik Roy

Tremendous progress has been made in sequential processing with the recent advances in recurrent neural networks. However, recurrent architectures face the challenge of exploding/v…

cs.NE20213 cited

One Timestep is All You Need: Training Spiking Neural Networks with Ultra Low Latency

Sayeed Shafayet Chowdhury, Nitin Rathi, Kaushik Roy

Spiking Neural Networks (SNNs) are energy efficient alternatives to commonly used deep neural networks (DNNs). Through event-driven information processing, SNNs can reduce the expe…

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.NE2020

DIET-SNN: Direct Input Encoding With Leakage and Threshold Optimization in Deep Spiking Neural Networks

Nitin Rathi, Kaushik Roy

Bio-inspired spiking neural networks (SNNs), operating with asynchronous binary signals (or spikes) distributed over time, can potentially lead to greater computational efficiency…

cs.NE2020

Towards Understanding the Effect of Leak in Spiking Neural Networks

Sayeed Shafayet Chowdhury, Chankyu Lee, Kaushik Roy

Spiking Neural Networks (SNNs) are being explored to emulate the astounding capabilities of human brain that can learn and compute functions robustly and efficiently with noisy spi…

cs.NE2020

Hyperparameter Optimization in Binary Communication Networks for Neuromorphic Deployment

Maryam Parsa, Catherine D. Schuman, Prasanna Date +8

Training neural networks for neuromorphic deployment is non-trivial. There have been a variety of approaches proposed to adapt back-propagation or back-propagation-like algorithms…