| Learning transferable architectures for scalable image recognition B Zoph, V Vasudevan, J Shlens, QV Le Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 4244 | 2018 |
| Neural architecture search with reinforcement learning B Zoph, QV Le arXiv preprint arXiv:1611.01578, 2016 | 4075 | 2016 |
| Searching for activation functions P Ramachandran, B Zoph, QV Le arXiv preprint arXiv:1710.05941, 2017 | 2186* | 2017 |
| Autoaugment: Learning augmentation strategies from data ED Cubuk*, B Zoph*, D Mane, V Vasudevan, QV Le Proceedings of the IEEE conference on computer vision and pattern …, 2019 | 2014* | 2019 |
| Efficient neural architecture search via parameters sharing H Pham, M Guan, B Zoph, Q Le, J Dean International conference on machine learning, 4095-4104, 2018 | 1966 | 2018 |
| Specaugment: A simple data augmentation method for automatic speech recognition DS Park, W Chan, Y Zhang, CC Chiu, B Zoph, ED Cubuk, QV Le arXiv preprint arXiv:1904.08779, 2019 | 1724 | 2019 |
| Progressive neural architecture search C Liu, B Zoph, M Neumann, J Shlens, W Hua, LJ Li, L Fei-Fei, A Yuille, ... Proceedings of the European conference on computer vision (ECCV), 19-34, 2018 | 1501 | 2018 |
| Randaugment: Practical automated data augmentation with a reduced search space ED Cubuk*, B Zoph*, J Shlens, QV Le arXiv preprint arXiv:1909.13719, 2019 | 1016* | 2019 |
| Transfer learning for low-resource neural machine translation B Zoph, D Yuret, J May, K Knight arXiv preprint arXiv:1604.02201, 2016 | 631 | 2016 |
| Attention augmented convolutional networks I Bello, B Zoph, A Vaswani, J Shlens, QV Le Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 542 | 2019 |
| Understanding and simplifying one-shot architecture search G Bender, PJ Kindermans, B Zoph, V Vasudevan, Q Le International Conference on Machine Learning, 550-559, 2018 | 507 | 2018 |
| Augmix: A simple data processing method to improve robustness and uncertainty D Hendrycks, N Mu, ED Cubuk, B Zoph, J Gilmer, B Lakshminarayanan arXiv preprint arXiv:1912.02781, 2019 | 445* | 2019 |
| Searching for efficient multi-scale architectures for dense image prediction LC Chen, M Collins, Y Zhu, G Papandreou, B Zoph, F Schroff, H Adam, ... Advances in neural information processing systems 31, 2018 | 334 | 2018 |
| Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity W Fedus*, B Zoph*, N Shazeer arXiv preprint arXiv:2101.03961, 2021 | 296 | 2021 |
| Neural optimizer search with reinforcement learning I Bello, B Zoph, V Vasudevan, QV Le International Conference on Machine Learning, 459-468, 2017 | 289 | 2017 |
| Multi-source neural translation B Zoph, K Knight arXiv preprint arXiv:1601.00710, 2016 | 288 | 2016 |
| Learning data augmentation strategies for object detection B Zoph*, ED Cubuk*, G Ghiasi, TY Lin, J Shlens, QV Le arXiv preprint arXiv:1906.11172, 2019 | 277 | 2019 |
| Rethinking pre-training and self-training B Zoph*, G Ghiasi*, TY Lin*, Y Cui, H Liu, ED Cubuk, QV Le arXiv preprint arXiv:2006.06882, 2020 | 276 | 2020 |
| Simple Copy-Paste is a Strong Data Augmentation Method for Instance Segmentation G Ghiasi*, Y Cui*, A Srinivas*, R Qian, TY Lin, ED Cubuk, QV Le, B Zoph arXiv preprint arXiv:2012.07177, 2020 | 181 | 2020 |
| Naive-student: Leveraging semi-supervised learning in video sequences for urban scene segmentation LC Chen, RG Lopes, B Cheng, MD Collins, ED Cubuk, B Zoph, H Adam, ... European Conference on Computer Vision, 695-714, 2020 | 72 | 2020 |
Quoc V. LeResearch Scientist, Google BrainVerified email at stanford.edu
