| Robust RRAM-based in-memory computing in light of model stability G Krishnan, J Sun, J Hazra, X Du, M Liehr, Z Li, K Beckmann, RV Joshi, ... 2021 IEEE International Reliability Physics Symposium (IRPS), 1-5, 2021 | 15 | 2021 |
| Gradient-based novelty detection boosted by self-supervised binary classification J Sun, L Yang, J Zhang, F Liu, M Halappanavar, D Fan, Y Cao Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8370-8377, 2022 | 14 | 2022 |
| Exploring model stability of deep neural networks for reliable RRAM-based in-memory acceleration G Krishnan, L Yang, J Sun, J Hazra, X Du, M Liehr, Z Li, K Beckmann, ... IEEE Transactions on Computers 71 (11), 2740-2752, 2022 | 9 | 2022 |
| Evolutionary NAS in light of model stability for accurate continual learning X Du, Z Li, J Sun, F Liu, Y Cao 2021 international joint conference on neural networks (IJCNN), 1-8, 2021 | 3 | 2021 |
| Exploiting 2.5 D/3D Heterogeneous Integration for AI Computing Z Wang, J Sun, A Goksoy, SK Mandal, Y Liu, J Seo, C Chakrabarti, ... 2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC), 758-764, 2024 | 1 | 2024 |
| Overview of Recent Advancements in Deep Learning and Artificial Intelligence V Narayanan, Y Cao, P Panda, N Reddy Challapalle, X Du, Y Kim, ... Advances in Electromagnetics Empowered by Artificial Intelligence and Deep …, 2023 | 1 | 2023 |
| Benchmarking Heterogeneous Integration with 2.5 D/3D Interconnect Modeling Z Wang, J Sun, A Goksoy, SK Mandal, JS Seo, C Chakrabarti, UY Ogras, ... 2023 IEEE 15th International Conference on ASIC (ASICON), 1-4, 2023 | | 2023 |
| Reliable RRAM-based In-Memory Computing in Light of Model Stability G Krishnan, L Yang, J Sun, J Hazra, X Du, M Liehr, K Beckmann, R Joshi, ... ACM/IEEE Design Automation Conference, 2021 | | 2021 |
| Self-supervised Novelty Detection for Continual Learning: A Gradient-Based Approach Boosted by Binary Classification J Sun, L Yang, J Zhang, F Liu, M Halappanavar, D Fan, Y Cao International Workshop on Continual Semi-Supervised Learning, 118-133, 2021 | | 2021 |
| Continual Graph Learning for Thermal Analysis of Composite Materials under Interface Variations J Sun, Z Wang, F Liu, V Chhabria, Y Cao | | |
| Self-supervised Continual Learning based on Batch-mode Novelty Detection J Sun, J Zhang, FY Liu, MM Halappanavar, D Fan, Y Cao | | |
Yu CaoProfessor, University of Minnesota在 umn.edu 的电子邮件经过验证
