| How convolutional neural network see the world-A survey of convolutional neural network visualization methods Z Qin, F Yu, C Liu, X Chen arXiv preprint arXiv:1804.11191, 2018 | 304 | 2018 |
| Rescuing memristor-based neuromorphic design with high defects C Liu, M Hu, JP Strachan, H Li Proceedings of the 54th Annual Design Automation Conference 2017, 1-6, 2017 | 277 | 2017 |
| A spiking neuromorphic design with resistive crossbar C Liu, B Yan, C Yang, L Song, Z Li, B Liu, Y Chen, H Li, Q Wu, H Jiang Proceedings of the 52nd Annual Design Automation Conference, 1-6, 2015 | 160 | 2015 |
| Effect of flexoelectricity on electrostatic potential in a bent piezoelectric nanowire C Liu, S Hu, S Shen Smart materials and structures 21 (11), 115024, 2012 | 97 | 2012 |
| Fed2: Feature-aligned federated learning F Yu, W Zhang, Z Qin, Z Xu, D Wang, C Liu, Z Tian, X Chen Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 78 | 2021 |
| Interpreting and evaluating neural network robustness F Yu, Z Qin, C Liu, L Zhao, Y Wang, X Chen arXiv preprint arXiv:1905.04270, 2019 | 74 | 2019 |
| A memristor crossbar based computing engine optimized for high speed and accuracy C Liu, Q Yang, B Yan, J Yang, X Du, W Zhu, H Jiang, Q Wu, M Barnell, ... 2016 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 110-115, 2016 | 52 | 2016 |
| Automated runtime-aware scheduling for multi-tenant DNN inference on GPU F Yu, S Bray, D Wang, L Shangguan, X Tang, C Liu, X Chen 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 1-9, 2021 | 50 | 2021 |
| Heterogeneous federated learning F Yu, W Zhang, Z Qin, Z Xu, D Wang, C Liu, Z Tian, X Chen arXiv preprint arXiv:2008.06767, 2020 | 46 | 2020 |
| Looking ahead for resistive memory technology: A broad perspective on reram technology for future storage and computing HH Li, Y Chen, C Liu, JP Strachan, N Davila IEEE Consumer Electronics Magazine 6 (1), 94-103, 2016 | 46 | 2016 |
| Reform: Static and dynamic resource-aware dnn reconfiguration framework for mobile device Z Xu, F Yu, C Liu, X Chen Proceedings of the 56th Annual Design Automation Conference 2019, 1-6, 2019 | 44 | 2019 |
| A memristor-based neuromorphic engine with a current sensing scheme for artificial neural network applications C Liu, Q Yang, C Zhang, H Jiang, Q Wu, HH Li 2017 22nd Asia and South Pacific Design Automation Conference (ASP-DAC), 647-652, 2017 | 38 | 2017 |
| Interpreting adversarial robustness: A view from decision surface in input space F Yu, C Liu, Y Wang, L Zhao, X Chen arXiv preprint arXiv:1810.00144, 2018 | 36 | 2018 |
| A weighted sensing scheme for ReRAM-based cross-point memory array C Liu, H Li 2014 IEEE Computer Society Annual Symposium on VLSI, 65-70, 2014 | 35 | 2014 |
| A survey of multi-tenant deep learning inference on gpu F Yu, D Wang, L Shangguan, M Zhang, C Liu, X Chen arXiv preprint arXiv:2203.09040, 2022 | 34 | 2022 |
| REIN the RobuTS: Robust DNN-based image recognition in autonomous driving systems F Yu, Z Qin, C Liu, D Wang, X Chen IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2020 | 29 | 2020 |
| Rescuing memristor-based neuromorphic design with high defects. In2017 54th ACM/EDAC/IEEE Design Automation Conference (DAC) 2017 Jun 18 (pp. 1-6) C Liu, M Hu, JP Strachan, H Li IEEE, 0 | 28 | |
| Build reliable and efficient neuromorphic design with memristor technology B Li, B Yan, C Liu, H Li Proceedings of the 24th Asia and South Pacific Design Automation Conference …, 2019 | 27 | 2019 |
| Understanding the trade-offs of device, circuit and application in ReRAM-based neuromorphic computing systems B Yan, C Liu, X Liu, Y Chen, H Li 2017 IEEE International Electron Devices Meeting (IEDM), 11.4. 1-11.4. 4, 2017 | 23 | 2017 |
| Directx: Dynamic resource-aware cnn reconfiguration framework for real-time mobile applications Z Xu, F Yu, Z Qin, C Liu, X Chen IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2020 | 19 | 2020 |
Xiang 'Shawn' ChenPeking UniversityПодтвержден адрес электронной почты в домене pku.edu.cn