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Neural Networks at the Edge.

, , , , , , и . SMARTCOMP, стр. 45-50. IEEE, (2019)

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Saiprasath Gopalakrishnan

Selvi Gopalakrishnan

Gopalakrishnan Venkiteswaran

Vijay Gopalakrishnan

R Srinivasan

 

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Convolutional Spike Timing Dependent Plasticity based Feature Learning in Spiking Neural Networks., , и . CoRR, (2017)sBSNN: Stochastic-Bits Enabled Binary Spiking Neural Network With On-Chip Learning for Energy Efficient Neuromorphic Computing at the Edge., , , и . IEEE Trans. Circuits Syst. I Regul. Pap., 67-I (8): 2546-2555 (2020)Deep Spiking Convolutional Neural Network Trained With Unsupervised Spike-Timing-Dependent Plasticity., , , и . IEEE Trans. Cognitive and Developmental Systems, 11 (3): 384-394 (2019)Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation., , , и . CoRR, (2020)Enabling Homeostasis using Temporal Decay Mechanisms in Spiking CNNs Trained with Unsupervised Spike Timing Dependent Plasticity., , , и . IJCNN, стр. 1-8. IEEE, (2020)Invited - Cross-layer approximations for neuromorphic computing: from devices to circuits and systems., , , , , , и . DAC, стр. 98:1-98:6. ACM, (2016)Training Deep Spiking Neural Networks for Energy-Efficient Neuromorphic Computing., , , , , и . ICASSP, стр. 8549-8553. IEEE, (2020)Explicitly Trained Spiking Sparsity in Spiking Neural Networks with Backpropagation., , , и . CoRR, (2020)Reinforcement Learning with Low-Complexity Liquid State Machines., , и . CoRR, (2019)STDP-based Unsupervised Feature Learning using Convolution-over-time in Spiking Neural Networks for Energy-Efficient Neuromorphic Computing., , и . ACM J. Emerg. Technol. Comput. Syst., 14 (4): 44:1-44:12 (2018)