| Biological underpinnings for lifelong learning machines D Kudithipudi, M Aguilar-Simon, J Babb, M Bazhenov, D Blackiston, ... Nature Machine Intelligence 4 (3), 196-210, 2022 | 161 | 2022 |
| Deep positron: A deep neural network using the posit number system Z Carmichael, HF Langroudi, C Khazanov, J Lillie, JL Gustafson, ... 2019 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2019 | 123 | 2019 |
| Design and analysis of a neuromemristive reservoir computing architecture for biosignal processing D Kudithipudi, Q Saleh, C Merkel, J Thesing, B Wysocki Frontiers in neuroscience 9, 502, 2016 | 110 | 2016 |
| Deep learning inference on embedded devices: Fixed-point vs posit SHF Langroudi, T Pandit, D Kudithipudi 2018 1st Workshop on Energy Efficient Machine Learning and Cognitive …, 2018 | 71 | 2018 |
| Performance-efficiency trade-off of low-precision numerical formats in deep neural networks Z Carmichael, HF Langroudi, C Khazanov, J Lillie, JL Gustafson, ... Proceedings of the conference for next generation arithmetic 2019, 1-9, 2019 | 67 | 2019 |
| Memristor-based neural logic blocks for nonlinearly separable functions M Soltiz, D Kudithipudi, C Merkel, GS Rose, RE Pino IEEE Transactions on computers 62 (8), 1597-1606, 2013 | 61 | 2013 |
| GALEOR: Leakage reduction for CMOS circuits S Katrue, D Kudithipudi 2008 15th IEEE International Conference on Electronics, Circuits and Systems …, 2008 | 54 | 2008 |
| Deep liquid state machines with neural plasticity for video activity recognition N Soures, D Kudithipudi Frontiers in neuroscience 13, 686, 2019 | 52 | 2019 |
| SIRNet: understanding social distancing measures with hybrid neural network model for COVID-19 infectious spread N Soures, D Chambers, Z Carmichael, A Daram, DP Shah, K Clark, ... arXiv preprint arXiv:2004.10376, 2020 | 49 | 2020 |
| Reconfigurable N-level memristor memory design CE Merkel, N Nagpal, S Mandalapu, D Kudithipudi The 2011 International Joint Conference on Neural Networks, 3042-3048, 2011 | 47 | 2011 |
| HTM spatial pooler with memristor crossbar circuits for sparse biometric recognition AP James, I Fedorova, T Ibrayev, D Kudithipudi IEEE Transactions on Biomedical Circuits and Systems 11 (3), 640-651, 2017 | 45 | 2017 |
| A mathematical formalization of hierarchical temporal memory’s spatial pooler J Mnatzaganian, E Fokoué, D Kudithipudi Frontiers in Robotics and AI 3, 81, 2017 | 43 | 2017 |
| Memristive reservoir computing architecture for epileptic seizure detection C Merkel, Q Saleh, C Donahue, D Kudithipudi Procedia Computer Science 41, 249-254, 2014 | 42 | 2014 |
| Neuromemristive systems: boosting efficiency through brain-inspired computing C Merkel, R Hasan, N Soures, D Kudithipudi, T Taha, S Agarwal, ... Computer 49 (10), 56-64, 2016 | 34 | 2016 |
| Implementation of low power digital multipliers using 10 transistor adder blocks D Kudithipudi, E John Journal of Low Power Electronics 1 (3), 286-296, 2005 | 34 | 2005 |
| On the statistical challenges of echo state networks and some potential remedies Q Wu, E Fokoue, D Kudithipudi arXiv preprint arXiv:1802.07369, 2018 | 33 | 2018 |
| Positnn framework: Tapered precision deep learning inference for the edge HF Langroudi, Z Carmichael, JL Gustafson, D Kudithipudi 2019 IEEE Space Computing Conference (SCC), 53-59, 2019 | 32 | 2019 |
| Neuromorphic architecture for the hierarchical temporal memory AM Zyarah, D Kudithipudi IEEE Transactions on Emerging Topics in Computational Intelligence 3 (1), 4-14, 2019 | 32 | 2019 |
| Adaptive posit: Parameter aware numerical format for deep learning inference on the edge HF Langroudi, V Karia, JL Gustafson, D Kudithipudi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 31 | 2020 |
| Robustness of a memristor based liquid state machine N Soures, L Hays, D Kudithipudi 2017 international joint conference on neural networks (ijcnn), 2414-2420, 2017 | 31 | 2017 |
Cory MerkelBrain Lab, Rochester Institute of Technology在 rit.edu 的电子邮件经过验证
Cory MerkelBrain Lab, Rochester Institute of Technology在 rit.edu 的电子邮件经过验证