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ORCIDGopalakrishnan Srinivasan
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2020 – today
- 2021
[c13]Yinghan Long
, Indranil Chakraborty, Gopalakrishnan Srinivasan, Kaushik Roy:
Complexity-aware Adaptive Training and Inference for Edge-Cloud Distributed AI Systems. ICDCS 2021: 573-583- [i12]Yinghan Long, Indranil Chakraborty, Gopalakrishnan Srinivasan, Kaushik Roy:
Complexity-aware Adaptive Training and Inference for Edge-Cloud Distributed AI Systems. CoRR abs/2109.06440 (2021) - 2020
- [j7]Minsuk Koo, Gopalakrishnan Srinivasan, Yong Shim, Kaushik Roy:
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. 67-I(8): 2546-2555 (2020) - [j6]Amogh Agrawal, Indranil Chakraborty, Deboleena Roy, Utkarsh Saxena, Saima Sharmin, Minsuk Koo, Yong Shim, Gopalakrishnan Srinivasan, Chamika M. Liyanagedera, Abhronil Sengupta, Kaushik Roy:
Revisiting Stochastic Computing in the Era of Nanoscale Nonvolatile Technologies. IEEE Trans. Very Large Scale Integr. Syst. 28(12): 2481-2494 (2020) - [c12]Bing Han, Gopalakrishnan Srinivasan, Kaushik Roy:
RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network. CVPR 2020: 13555-13564 - [c11]Gopalakrishnan Srinivasan, Chankyu Lee, Abhronil Sengupta, Priyadarshini Panda, Syed Shakib Sarwar, Kaushik Roy:
Training Deep Spiking Neural Networks for Energy-Efficient Neuromorphic Computing. ICASSP 2020: 8549-8553 - [c10]Nitin Rathi, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy:
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation. ICLR 2020 - [c9]Krishna Reddy Kesari, Priyadarshini Panda, Gopalakrishnan Srinivasan, Kaushik Roy:
Enabling Homeostasis using Temporal Decay Mechanisms in Spiking CNNs Trained with Unsupervised Spike Timing Dependent Plasticity. IJCNN 2020: 1-8 - [c8]Sourjya Roy, Priyadarshini Panda, Gopalakrishnan Srinivasan, Anand Raghunathan:
Pruning Filters while Training for Efficiently Optimizing Deep Learning Networks. IJCNN 2020: 1-7 - [i11]Minsuk Koo, Gopalakrishnan Srinivasan, Yong Shim, Kaushik Roy:
sBSNN: Stochastic-Bits Enabled Binary Spiking Neural Network with On-Chip Learning for Energy Efficient Neuromorphic Computing at the Edge. CoRR abs/2002.11163 (2020) - [i10]Jason M. Allred, Steven J. Spencer, Gopalakrishnan Srinivasan, Kaushik Roy:
Explicitly Trained Spiking Sparsity in Spiking Neural Networks with Backpropagation. CoRR abs/2003.01250 (2020) - [i9]Bing Han, Gopalakrishnan Srinivasan, Kaushik Roy:
RMP-SNNs: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Networks. CoRR abs/2003.01811 (2020) - [i8]Sourjya Roy, Priyadarshini Panda, Gopalakrishnan Srinivasan, Anand Raghunathan:
Pruning Filters while Training for Efficiently Optimizing Deep Learning Networks. CoRR abs/2003.02800 (2020) - [i7]Nitin Rathi, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy:
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation. CoRR abs/2005.01807 (2020)
2010 – 2019
- 2019
- [j5]Yinghan Long, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy:
Structured Learning for Action Recognition in Videos. IEEE J. Emerg. Sel. Topics Circuits Syst. 9(3): 475-484 (2019) - [j4]Chankyu Lee, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy:
Deep Spiking Convolutional Neural Network Trained With Unsupervised Spike-Timing-Dependent Plasticity. IEEE Trans. Cogn. Dev. Syst. 11(3): 384-394 (2019) - [j3]Amogh Agrawal, Akhilesh Jaiswal, Deboleena Roy, Bing Han, Gopalakrishnan Srinivasan, Aayush Ankit, Kaushik Roy:
Xcel-RAM: Accelerating Binary Neural Networks in High-Throughput SRAM Compute Arrays. IEEE Trans. Circuits Syst. I Regul. Pap. 66-I(8): 3064-3076 (2019) - [c7]Deboleena Roy, Gopalakrishnan Srinivasan, Priyadarshini Panda, Richard Tomsett, Nirmit Desai, Raghu K. Ganti, Kaushik Roy:
Neural Networks at the Edge. SMARTCOMP 2019: 45-50 - [i6]Gopalakrishnan Srinivasan, Kaushik Roy:
ReStoCNet: Residual Stochastic Binary Convolutional Spiking Neural Network for Memory-Efficient Neuromorphic Computing. CoRR abs/1902.04161 (2019) - [i5]Wachirawit Ponghiran, Gopalakrishnan Srinivasan, Kaushik Roy:
Reinforcement Learning with Low-Complexity Liquid State Machines. CoRR abs/1906.01695 (2019) - 2018
- [j2]Syed Shakib Sarwar, Gopalakrishnan Srinivasan, Bing Han, Parami Wijesinghe, Akhilesh Jaiswal, Priyadarshini Panda, Anand Raghunathan, Kaushik Roy:
Energy Efficient Neural Computing: A Study of Cross-Layer Approximations. IEEE J. Emerg. Sel. Topics Circuits Syst. 8(4): 796-809 (2018) - [j1]Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy:
STDP-based Unsupervised Feature Learning using Convolution-over-time in Spiking Neural Networks for Energy-Efficient Neuromorphic Computing. ACM J. Emerg. Technol. Comput. Syst. 14(4): 44:1-44:12 (2018) - [i4]Amogh Agrawal, Akhilesh Jaiswal, Bing Han, Gopalakrishnan Srinivasan, Kaushik Roy:
Xcel-RAM: Accelerating Binary Neural Networks in High-Throughput SRAM Compute Arrays. CoRR abs/1807.00343 (2018) - 2017
- [c6]Gopalakrishnan Srinivasan, Abhronil Sengupta, Kaushik Roy:
Magnetic tunnel junction enabled all-spin stochastic spiking neural network. DATE 2017: 530-535 - [c5]Gopalakrishnan Srinivasan, Sourjya Roy, Vijay Raghunathan, Kaushik Roy:
Spike timing dependent plasticity based enhanced self-learning for efficient pattern recognition in spiking neural networks. IJCNN 2017: 1847-1854 - [c4]Priyadarshini Panda, Gopalakrishnan Srinivasan, Kaushik Roy:
EnsembleSNN: Distributed assistive STDP learning for energy-efficient recognition in spiking neural networks. IJCNN 2017: 2629-2635 - [i3]Priyadarshini Panda, Gopalakrishnan Srinivasan, Kaushik Roy:
Convolutional Spike Timing Dependent Plasticity based Feature Learning in Spiking Neural Networks. CoRR abs/1703.03854 (2017) - 2016
- [c3]Priyadarshini Panda, Abhronil Sengupta, Syed Shakib Sarwar, Gopalakrishnan Srinivasan, Swagath Venkataramani, Anand Raghunathan, Kaushik Roy:
Invited - Cross-layer approximations for neuromorphic computing: from devices to circuits and systems. DAC 2016: 98:1-98:6 - [c2]Gopalakrishnan Srinivasan, Parami Wijesinghe, Syed Shakib Sarwar, Akhilesh Jaiswal, Kaushik Roy:
Significance driven hybrid 8T-6T SRAM for energy-efficient synaptic storage in artificial neural networks. DATE 2016: 151-156 - [i2]Gopalakrishnan Srinivasan, Parami Wijesinghe, Syed Shakib Sarwar, Akhilesh Jaiswal, Kaushik Roy:
Significance Driven Hybrid 8T-6T SRAM for Energy-Efficient Synaptic Storage in Artificial Neural Networks. CoRR abs/1602.08556 (2016) - [i1]Akhilesh Jaiswal, Sourjya Roy, Gopalakrishnan Srinivasan, Kaushik Roy:
Proposal for a Leaky-Integrate-Fire Spiking Neuron based on Magneto-Electric Switching of Ferro-magnets. CoRR abs/1609.09158 (2016)
2000 – 2009
- 2005
- [c1]D. Roy Mahapatra, Debi Prasad Ghosh, Gopalakrishnan Srinivasan:
Multiscale Finite Element Modeling of the Coupled Nonlinear Dynamics of Magnetostrictive Composite Thin Film. International Conference on Computational Science (3) 2005: 1-8
Coauthor Index
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