| Enabling spike-based backpropagation for training deep neural network architectures C Lee, SS Sarwar, P Panda, G Srinivasan, K Roy Frontiers in neuroscience 14, 497482, 2020 | 407 | 2020 |
| Rmp-snn: Residual membrane potential neuron for enabling deeper high-accuracy and low-latency spiking neural network B Han, G Srinivasan, K Roy Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 335 | 2020 |
| Enabling deep spiking neural networks with hybrid conversion and spike timing dependent backpropagation N Rathi, G Srinivasan, P Panda, K Roy International Conference on Learning Representations (ICLR), 2020 | 314 | 2020 |
| Magnetic tunnel junction based long-term short-term stochastic synapse for a spiking neural network with on-chip STDP learning G Srinivasan, A Sengupta, K Roy Scientific reports 6 (1), 29545, 2016 | 229 | 2016 |
| Training deep spiking convolutional neural networks with STDP-based unsupervised pre-training followed by supervised fine-tuning C Lee, P Panda, G Srinivasan, K Roy Frontiers in neuroscience 12, 435, 2018 | 217 | 2018 |
| Deep spiking convolutional neural network trained with unsupervised spike-timing-dependent plasticity C Lee, G Srinivasan, P Panda, K Roy IEEE Transactions on Cognitive and Developmental Systems 11 (3), 384-394, 2018 | 152 | 2018 |
| Xcel-RAM: Accelerating binary neural networks in high-throughput SRAM compute arrays A Agrawal, A Jaiswal, D Roy, B Han, G Srinivasan, A Ankit, K Roy IEEE Transactions on Circuits and Systems I: Regular Papers 66 (8), 3064-3076, 2019 | 117 | 2019 |
| Proposal for a leaky-integrate-fire spiking neuron based on magnetoelectric switching of ferromagnets A Jaiswal, S Roy, G Srinivasan, K Roy IEEE Transactions on Electron Devices 64 (4), 1818-1824, 2017 | 81 | 2017 |
| Restocnet: Residual stochastic binary convolutional spiking neural network for memory-efficient neuromorphic computing G Srinivasan, K Roy Frontiers in neuroscience 13, 189, 2019 | 74 | 2019 |
| Stdp-based unsupervised feature learning using convolution-over-time in spiking neural networks for energy-efficient neuromorphic computing G Srinivasan, P Panda, K Roy ACM Journal on Emerging Technologies in Computing Systems (JETC) 14 (4), 1-12, 2018 | 68* | 2018 |
| Perovskite neural trees HT Zhang, TJ Park, IA Zaluzhnyy, Q Wang, SN Wadekar, S Manna, ... Nature communications 11 (1), 2245, 2020 | 55 | 2020 |
| Analysis of liquid ensembles for enhancing the performance and accuracy of liquid state machines P Wijesinghe, G Srinivasan, P Panda, K Roy Frontiers in neuroscience 13, 504, 2019 | 54 | 2019 |
| Energy efficient neural computing: A study of cross-layer approximations SS Sarwar, G Srinivasan, B Han, P Wijesinghe, A Jaiswal, P Panda, ... IEEE Journal on Emerging and Selected Topics in Circuits and Systems 8 (4 …, 2018 | 51 | 2018 |
| Magnetic tunnel junction enabled all-spin stochastic spiking neural network G Srinivasan, A Sengupta, K Roy Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017 …, 2017 | 47 | 2017 |
| Cross-layer approximations for neuromorphic computing: From devices to circuits and systems P Panda, A Sengupta, SS Sarwar, G Srinivasan, S Venkataramani, ... Proceedings of the 53rd Annual Design Automation Conference, 1-6, 2016 | 46 | 2016 |
| Significance driven hybrid 8T-6T SRAM for energy-efficient synaptic storage in artificial neural networks G Srinivasan, P Wijesinghe, SS Sarwar, A Jaiswal, K Roy 2016 Design, Automation & Test in Europe Conference & Exhibition (DATE), 151-156, 2016 | 46 | 2016 |
| Spilinc: Spiking liquid-ensemble computing for unsupervised speech and image recognition G Srinivasan, P Panda, K Roy Frontiers in neuroscience 12, 524, 2018 | 41 | 2018 |
| SBSNN: Stochastic-bits enabled binary spiking neural network with on-chip learning for energy efficient neuromorphic computing at the edge M Koo, G Srinivasan, Y Shim, K Roy IEEE Transactions on Circuits and Systems I: Regular Papers 67 (8), 2546-2555, 2020 | 39 | 2020 |
| Pruning filters while training for efficiently optimizing deep learning networks S Roy, P Panda, G Srinivasan, A Raghunathan 2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020 | 30 | 2020 |
| Spike timing dependent plasticity based enhanced self-learning for efficient pattern recognition in spiking neural networks G Srinivasan, S Roy, V Raghunathan, K Roy 2017 International Joint Conference on Neural Networks (IJCNN), 1847-1854, 2017 | 28 | 2017 |
Kaushik RoyProfessor of Electrical and Computer Engineering, Purdue University在 purdue.edu 的电子邮件经过验证
