| Efficientnet: Rethinking model scaling for convolutional neural networks M Tan, Q Le International conference on machine learning, 6105-6114, 2019 | 6495 | 2019 |
| Searching for mobilenetv3 A Howard, M Sandler, G Chu, LC Chen, B Chen, M Tan, W Wang, Y Zhu, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 2081 | 2019 |
| Mnasnet: Platform-aware neural architecture search for mobile M Tan, B Chen, R Pang, V Vasudevan, M Sandler, A Howard, QV Le Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 1822 | 2019 |
| Efficientdet: Scalable and efficient object detection M Tan, R Pang, QV Le Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 1789 | 2020 |
| Adversarial examples improve image recognition C Xie, M Tan, B Gong, J Wang, AL Yuille, QV Le Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 263 | 2020 |
| MixConv: Mixed Depthwise Convolutional Kernels M Tan, QV Le Proceedings of the 30th British Machine Vision Conference (BMVC), 2019 | 211* | 2019 |
| Efficientnetv2: Smaller models and faster training M Tan, QV Le International Conference on Machine Learning, 2021 | 207 | 2021 |
| Spinenet: Learning scale-permuted backbone for recognition and localization X Du, TY Lin, P Jin, G Ghiasi, M Tan, Y Cui, QV Le, X Song Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 129 | 2020 |
| Bignas: Scaling up neural architecture search with big single-stage models J Yu, P Jin, H Liu, G Bender, PJ Kindermans, M Tan, T Huang, X Song, ... European Conference on Computer Vision, 702-717, 2020 | 125 | 2020 |
| Coatnet: Marrying convolution and attention for all data sizes Z Dai, H Liu, QV Le, M Tan Advances in Neural Information Processing Systems 34, 3965-3977, 2021 | 117 | 2021 |
| Efficientnet: Rethinking model scaling for convolutional neural 373 networks M Tan, Q Le International Conference on Machine Learning, 6105-6114, 0 | 87 | |
| Smooth adversarial training C Xie, M Tan, B Gong, A Yuille, QV Le arXiv preprint arXiv:2006.14536, 2020 | 79 | 2020 |
| Assemblenet: Searching for multi-stream neural connectivity in video architectures MS Ryoo, AJ Piergiovanni, M Tan, A Angelova European Conference on Computer Vision (ECCV), 2019 | 76 | 2019 |
| Nyströmformer: A Nystöm-based Algorithm for Approximating Self-Attention Y Xiong, Z Zeng, R Chakraborty, M Tan, G Fung, Y Li, V Singh Proceedings of the... AAAI Conference on Artificial Intelligence. AAAI …, 2021 | 75 | 2021 |
| Elasticflow: A complexity-effective approach for pipelining irregular loop nests M Tan, G Liu, R Zhao, S Dai, Z Zhang 2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 78-85, 2015 | 53 | 2015 |
| Mobiledets: Searching for object detection architectures for mobile accelerators Y Xiong, H Liu, S Gupta, B Akin, G Bender, Y Wang, PJ Kindermans, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 42 | 2021 |
| Search to distill: Pearls are everywhere but not the eyes Y Liu, X Jia, M Tan, R Vemulapalli, Y Zhu, B Green, X Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 40 | 2020 |
| Bit-level optimization for high-level synthesis and FPGA-based acceleration J Zhang, Z Zhang, S Zhou, M Tan, X Liu, X Cheng, J Cong Proceedings of the 18th annual ACM/SIGDA international symposium on Field …, 2010 | 39 | 2010 |
| Architectural specialization for inter-iteration loop dependence patterns S Srinath, B Ilbeyi, M Tan, G Liu, Z Zhang, C Batten 2014 47th Annual IEEE/ACM International Symposium on Microarchitecture, 583-595, 2014 | 38 | 2014 |
| Multithreaded pipeline synthesis for data-parallel kernels M Tan, B Liu, S Dai, Z Zhang 2014 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 718-725, 2014 | 37 | 2014 |
Quoc V. LeResearch Scientist, Google BrainVerified email at stanford.edu
