Gopalakrishnan Srinivasan
Orcid: 0000-0003-2015-8545
According to our database1,
Gopalakrishnan Srinivasan
authored at least 28 papers
between 2005 and 2024.
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Bibliography
2024
QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities.
CoRR, 2024
2021
Complexity-aware Adaptive Training and Inference for Edge-Cloud Distributed AI Systems.
Proceedings of the 41st IEEE International Conference on Distributed Computing Systems, 2021
2020
IEEE Trans. Very Large Scale Integr. Syst., 2020
sBSNN: Stochastic-Bits Enabled Binary Spiking Neural Network With On-Chip Learning for Energy Efficient Neuromorphic Computing at the Edge.
IEEE Trans. Circuits Syst. I Regul. Pap., 2020
RMP-SNNs: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Networks.
CoRR, 2020
CoRR, 2020
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Enabling Homeostasis using Temporal Decay Mechanisms in Spiking CNNs Trained with Unsupervised Spike Timing Dependent Plasticity.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation.
Proceedings of the 8th International Conference on Learning Representations, 2020
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020
2019
Xcel-RAM: Accelerating Binary Neural Networks in High-Throughput SRAM Compute Arrays.
IEEE Trans. Circuits Syst. I Regul. Pap., 2019
Deep Spiking Convolutional Neural Network Trained With Unsupervised Spike-Timing-Dependent Plasticity.
IEEE Trans. Cogn. Dev. Syst., 2019
IEEE J. Emerg. Sel. Topics Circuits Syst., 2019
ReStoCNet: Residual Stochastic Binary Convolutional Spiking Neural Network for Memory-Efficient Neuromorphic Computing.
CoRR, 2019
Proceedings of the IEEE International Conference on Smart Computing, 2019
2018
STDP-based Unsupervised Feature Learning using Convolution-over-time in Spiking Neural Networks for Energy-Efficient Neuromorphic Computing.
ACM J. Emerg. Technol. Comput. Syst., 2018
IEEE J. Emerg. Sel. Topics Circuits Syst., 2018
Xcel-RAM: Accelerating Binary Neural Networks in High-Throughput SRAM Compute Arrays.
CoRR, 2018
2017
Convolutional Spike Timing Dependent Plasticity based Feature Learning in Spiking Neural Networks.
CoRR, 2017
Spike timing dependent plasticity based enhanced self-learning for efficient pattern recognition in spiking neural networks.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017
EnsembleSNN: Distributed assistive STDP learning for energy-efficient recognition in spiking neural networks.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017
Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2017
2016
Proposal for a Leaky-Integrate-Fire Spiking Neuron based on Magneto-Electric Switching of Ferro-magnets.
CoRR, 2016
Significance driven hybrid 8T-6T SRAM for energy-efficient synaptic storage in artificial neural networks.
Proceedings of the 2016 Design, Automation & Test in Europe Conference & Exhibition, 2016
Invited - Cross-layer approximations for neuromorphic computing: from devices to circuits and systems.
Proceedings of the 53rd Annual Design Automation Conference, 2016
2005
Multiscale Finite Element Modeling of the Coupled Nonlinear Dynamics of Magnetostrictive Composite Thin Film.
Proceedings of the Computational Science, 2005