| {TVM}: An automated {End-to-End} optimizing compiler for deep learning T Chen, T Moreau, Z Jiang, L Zheng, E Yan, H Shen, M Cowan, L Wang, ... 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2018 | 1669 | 2018 |
| Learning to optimize tensor programs T Chen, L Zheng, E Yan, Z Jiang, T Moreau, L Ceze, C Guestrin, ... Advances in Neural Information Processing Systems 31, 2018 | 407 | 2018 |
| TVM: end-to-end optimization stack for deep learning T Chen, T Moreau, Z Jiang, H Shen, EQ Yan, L Wang, Y Hu, L Ceze, ... arXiv preprint arXiv:1802.04799 11 (2018), 20, 2018 | 264 | 2018 |
| A hardware–software blueprint for flexible deep learning specialization T Moreau, T Chen, L Vega, J Roesch, E Yan, L Zheng, J Fromm, Z Jiang, ... IEEE Micro 39 (5), 8-16, 2019 | 166 | 2019 |
| Characterizing structural regularities of labeled data in overparameterized models Z Jiang, C Zhang, K Talwar, MC Mozer arXiv preprint arXiv:2002.03206, 2020 | 79 | 2020 |
| VTA: an open hardware-software stack for deep learning T Moreau, T Chen, Z Jiang, L Ceze, C Guestrin, A Krishnamurthy arXiv preprint arXiv:1807.04188 10, 2018 | 78 | 2018 |
| MetaPhys: few-shot adaptation for non-contact physiological measurement X Liu, Z Jiang, J Fromm, X Xu, S Patel, D McDuff Proceedings of the conference on health, inference, and learning, 154-163, 2021 | 56 | 2021 |
| Efficientphys: Enabling simple, fast and accurate camera-based cardiac measurement X Liu, B Hill, Z Jiang, S Patel, D McDuff Proceedings of the IEEE/CVF winter conference on applications of computer …, 2023 | 44 | 2023 |
| Efficient deep learning inference on edge devices Z Jiang, T Chen, M Li Proceedings of ACM Conference on Systems and Machine Learning (SysML’18), 2018 | 41 | 2018 |
| Relay: A high-level compiler for deep learning J Roesch, S Lyubomirsky, M Kirisame, L Weber, J Pollock, L Vega, ... arXiv preprint arXiv:1904.08368, 2019 | 40 | 2019 |
| Splitsr: An end-to-end approach to super-resolution on mobile devices X Liu, Y Li, J Fromm, Y Wang, Z Jiang, A Mariakakis, S Patel Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2021 | 37 | 2021 |
| DietCode: Automatic optimization for dynamic tensor programs B Zheng, Z Jiang, CH Yu, H Shen, J Fromm, Y Liu, Y Wang, L Ceze, ... Proceedings of Machine Learning and Systems 4, 848-863, 2022 | 24 | 2022 |
| Efficientphys: Enabling simple, fast and accurate camera-based vitals measurement X Liu, BL Hill, Z Jiang, S Patel, D McDuff arXiv preprint arXiv:2110.04447, 2021 | 19 | 2021 |
| Exploring the memorization-generalization continuum in deep learning Z Jiang, C Zhang, K Talwar, MC Mozer arXiv preprint arXiv:2002.03206, 2020 | 18 | 2020 |
| Federated remote physiological measurement with imperfect data X Liu, M Zhang, Z Jiang, S Patel, D McDuff Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 8 | 2022 |
| Just-in-time dynamic-batching S Zha, Z Jiang, H Lin, Z Zhang arXiv preprint arXiv:1904.07421, 2019 | 3 | 2019 |
| MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs Z Jiang, H Lin, Y Zhong, Q Huang, Y Chen, Z Zhang, Y Peng, X Li, C Xie, ... arXiv preprint arXiv:2402.15627, 2024 | 2 | 2024 |
| Relax: Composable Abstractions for End-to-End Dynamic Machine Learning R Lai, J Shao, S Feng, SS Lyubomirsky, B Hou, W Lin, Z Ye, H Jin, Y Jin, ... arXiv preprint arXiv:2311.02103, 2023 | 2 | 2023 |
| Automated backend-aware post-training quantization Z Jiang, A Jain, A Liu, J Fromm, C Ma, T Chen, L Ceze arXiv preprint arXiv:2103.14949, 2021 | 2 | 2021 |
| Using Autotvm to Automatically Generate Deep Learning Libraries for Mobile Devices E Yan, T Chen, L Zheng, Z Jiang, T Moreau, C Guestrin, L Ceze, ... Proceedings of the 2nd SysML Conference, Palo Alto, CA, USA 31, 2019 | 2 | 2019 |
