| Designing neural network architectures using reinforcement learning B Baker, O Gupta, N Naik, R Raskar arXiv preprint arXiv:1611.02167, 2016 | 1889 | 2016 |
| Learning dexterous in-hand manipulation OAIM Andrychowicz, B Baker, M Chociej, R Jozefowicz, B McGrew, ... The International Journal of Robotics Research 39 (1), 3-20, 2020 | 1840 | 2020 |
| Emergent tool use from multi-agent autocurricula B Baker, I Kanitscheider, T Markov, Y Wu, G Powell, B McGrew, ... arXiv preprint arXiv:1909.07528, 2019 | 883 | 2019 |
| Multi-goal reinforcement learning: Challenging robotics environments and request for research M Plappert, M Andrychowicz, A Ray, B McGrew, B Baker, G Powell, ... arXiv preprint arXiv:1802.09464, 2018 | 598 | 2018 |
| Accelerating neural architecture search using performance prediction B Baker, O Gupta, R Raskar, N Naik arXiv preprint arXiv:1705.10823, 2017 | 468 | 2017 |
| Let's verify step by step H Lightman, V Kosaraju, Y Burda, H Edwards, B Baker, T Lee, J Leike, ... arXiv preprint arXiv:2305.20050, 2023 | 436 | 2023 |
| Video pretraining (vpt): Learning to act by watching unlabeled online videos B Baker, I Akkaya, P Zhokov, J Huizinga, J Tang, A Ecoffet, B Houghton, ... Advances in Neural Information Processing Systems 35, 24639-24654, 2022 | 269 | 2022 |
| Weak-to-strong generalization: Eliciting strong capabilities with weak supervision C Burns, P Izmailov, JH Kirchner, B Baker, L Gao, L Aschenbrenner, ... arXiv preprint arXiv:2312.09390, 2023 | 170 | 2023 |
| Determining the resolution limits of electron-beam lithography: direct measurement of the point-spread function VR Manfrinato, J Wen, L Zhang, Y Yang, RG Hobbs, B Baker, D Su, ... Nano letters 14 (8), 4406-4412, 2014 | 98 | 2014 |
| Use of machine-learning algorithms to determine features of systolic blood pressure variability that predict poor outcomes in hypertensive patients RC Lacson, B Baker, H Suresh, K Andriole, P Szolovits, E Lacson Jr Clinical kidney journal 12 (2), 206-212, 2019 | 48 | 2019 |
| Emergent reciprocity and team formation from randomized uncertain social preferences B Baker Advances in neural information processing systems 33, 15786-15799, 2020 | 34 | 2020 |
| Multi-task curriculum learning in a complex, visual, hard-exploration domain: Minecraft I Kanitscheider, J Huizinga, D Farhi, WH Guss, B Houghton, R Sampedro, ... arXiv preprint arXiv:2106.14876, 2021 | 20 | 2021 |
| Towards practical neural network meta-modeling B Baker Massachusetts Institute of Technology, 2017 | 1 | 2017 |
| Using machine learning to train and use a model to perform automatic interface actions based on video and input datasets B Baker, P Zhokhov, J Huizinga, J Tang, A Ecoffet, B Houghton, ... US Patent App. 18/545,722, 2024 | | 2024 |
| Using machine learning to train and use a model to perform automatic interface actions based on video and input datasets B Baker, I Akkaya, P Zhokhov, J Huizanga, J Tang, A Ecoffet, B Houghton, ... US Patent 11,887,367, 2024 | | 2024 |
| OpenAI 发布训练实体机器人的最新模拟环境 M PLAPPERT, M ANDRYCHOWICZ, A RAY, BOB MCGREW, B BAKER, ... 机器人产业, 2018 | | 2018 |
