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| nGraph-HE2: A high-throughput framework for neural network inference on encrypted data F Boemer, A Costache, R Cammarota, C Wierzynski Proceedings of the 7th ACM workshop on encrypted computing & applied …, 2019 | 201 | 2019 |
| Design of optical neural networks with component imprecisions MYS Fang, S Manipatruni, C Wierzynski, A Khosrowshahi, MR DeWeese Optics express 27 (10), 14009-14029, 2019 | 158 | 2019 |
| nGraph-HE: a graph compiler for deep learning on homomorphically encrypted data F Boemer, Y Lao, R Cammarota, C Wierzynski Proceedings of the 16th ACM international conference on computing frontiers …, 2019 | 148 | 2019 |
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| The challenges and opportunities of explainable AI C Wierzynski Intel. com 12, 2018 | 28 | 2018 |
| Value synchronization across neural processors MDN Canoy, Y Liu, VH Chan, M Campos, JA Levin, CM Wierzynski US Patent App. 14/163,893, 2015 | 26 | 2015 |
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| Optimizing user interface layouts via gradient descent P Duan, C Wierzynski, L Nachman Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems …, 2020 | 21 | 2020 |
| System And Method Of Dynamically Filtering Depth Estimates To Generate A Volumetric Map Of A Three-Dimensional Environment Having An Adjustable Maximum Depth CW Sweet III, C Wierzynski US Patent App. 15/676,245, 2018 | 15 | 2018 |
| Customized classifier over common features CM Wierzynski, DJ Julian, A Sarah US Patent App. 14/483,054, 2015 | 11 | 2015 |
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