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Gopalakrishnan Srinivasan

Complexity-aware Adaptive Training and Inference for Edge-Cloud Distributed AI Systems

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Sep 14, 2021
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Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation

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May 04, 2020
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Pruning Filters while Training for Efficiently Optimizing Deep Learning Networks

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Mar 05, 2020
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Explicitly Trained Spiking Sparsity in Spiking Neural Networks with Backpropagation

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Mar 02, 2020
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RMP-SNNs: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Networks

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Feb 25, 2020
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Reinforcement Learning with Low-Complexity Liquid State Machines

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Jun 04, 2019
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ReStoCNet: Residual Stochastic Binary Convolutional Spiking Neural Network for Memory-Efficient Neuromorphic Computing

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Feb 11, 2019
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Convolutional Spike Timing Dependent Plasticity based Feature Learning in Spiking Neural Networks

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Mar 20, 2017
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Proposal for a Leaky-Integrate-Fire Spiking Neuron based on Magneto-Electric Switching of Ferro-magnets

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Sep 29, 2016
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Significance Driven Hybrid 8T-6T SRAM for Energy-Efficient Synaptic Storage in Artificial Neural Networks

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Feb 27, 2016
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