| Going deeper in spiking neural networks: Vgg and residual architectures A Sengupta, Y Ye, R Wang, C Liu, K Roy Frontiers in neuroscience 13, 2019 | 1182 | 2019 |
| Spin-transfer torque devices for logic and memory: Prospects and perspectives X Fong, Y Kim, K Yogendra, D Fan, A Sengupta, A Raghunathan, K Roy IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2015 | 248 | 2015 |
| Proposal for an all-spin artificial neural network: Emulating neural and synaptic functionalities through domain wall motion in ferromagnets A Sengupta, Y Shim, K Roy IEEE transactions on biomedical circuits and systems 10 (6), 1152-1160, 2016 | 246 | 2016 |
| 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, 29545, 2016 | 237 | 2016 |
| Conditional deep learning for energy-efficient and enhanced pattern recognition P Panda, A Sengupta, K Roy 2016 design, automation & test in europe conference & exhibition (DATE), 475-480, 2016 | 225 | 2016 |
| Magnetic tunnel junction mimics stochastic cortical spiking neurons A Sengupta, P Panda, P Wijesinghe, Y Kim, K Roy Scientific Reports 6, 30039, 2016 | 220 | 2016 |
| Toward Fast Neural Computing using All-Photonic Phase Change Spiking Neurons I Chakraborty, G Saha, A Sengupta, K Roy Scientific reports 8 (1), 12980, 2018 | 209 | 2018 |
| Encoding neural and synaptic functionalities in electron spin: A pathway to efficient neuromorphic computing A Sengupta, K Roy Applied Physics Reviews 4 (4), 2017 | 155 | 2017 |
| Reconfigurable perovskite nickelate electronics for artificial intelligence HT Zhang, TJ Park, ANMN Islam, DSJ Tran, S Manna, Q Wang, S Mondal, ... Science 375 (6580), 533-539, 2022 | 146 | 2022 |
| Hybrid spintronic-cmos spiking neural network with on-chip learning: Devices, circuits, and systems A Sengupta, A Banerjee, K Roy Physical Review Applied 6 (6), 064003, 2016 | 135 | 2016 |
| RxNN: A framework for evaluating deep neural networks on resistive crossbars S Jain, A Sengupta, K Roy, A Raghunathan IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2020 | 131* | 2020 |
| Probabilistic deep spiking neural systems enabled by magnetic tunnel junction A Sengupta, M Parsa, B Han, K Roy IEEE Transactions on Electron Devices 63 (7), 2963 - 2970, 2016 | 127 | 2016 |
| Resparc: A reconfigurable and energy-efficient architecture with memristive crossbars for deep spiking neural networks A Ankit, A Sengupta, P Panda, K Roy Proceedings of the 54th Annual Design Automation Conference 2017, 1-6, 2017 | 124 | 2017 |
| Exploring the Connection Between Binary and Spiking Neural Networks S Lu, A Sengupta Frontiers in Neuroscience 14, 535, 2020 | 122 | 2020 |
| An all-memristor deep spiking neural computing system: A step toward realizing the low-power stochastic brain P Wijesinghe, A Ankit, A Sengupta, K Roy IEEE Transactions on Emerging Topics in Computational Intelligence 2 (5 …, 2018 | 116 | 2018 |
| Spin-orbit torque induced spike-timing dependent plasticity A Sengupta, Z Al Azim, X Fong, K Roy Applied Physics Letters 106 (9), 2015 | 107 | 2015 |
| Exploring neuromorphic computing based on spiking neural networks: Algorithms to hardware N Rathi, I Chakraborty, A Kosta, A Sengupta, A Ankit, P Panda, K Roy ACM Computing Surveys 55 (12), 1-49, 2023 | 106 | 2023 |
| A vision for all-spin neural networks: A device to system perspective A Sengupta, K Roy IEEE Transactions on Circuits and Systems I: Regular Papers 63 (12), 2267-2277, 2016 | 96 | 2016 |
| Spin orbit torque based electronic neuron A Sengupta, SH Choday, Y Kim, K Roy Applied Physics Letters 106 (14), 2015 | 89 | 2015 |
| Stochastic spiking neural networks enabled by magnetic tunnel junctions: From nontelegraphic to telegraphic switching regimes CM Liyanagedera, A Sengupta, A Jaiswal, K Roy Physical Review Applied 8 (6), 064017, 2017 | 85 | 2017 |
