| Palm-e: An embodied multimodal language model D Driess, F Xia, MSM Sajjadi, C Lynch, A Chowdhery, B Ichter, A Wahid, ... arXiv preprint arXiv:2303.03378, 2023 | 1409 | 2023 |
| Time-contrastive networks: Self-supervised learning from video P Sermanet, C Lynch, Y Chebotar, J Hsu, E Jang, S Schaal, S Levine, ... 2018 IEEE international conference on robotics and automation (ICRA), 1134-1141, 2018 | 1048 | 2018 |
| Bc-z: Zero-shot task generalization with robotic imitation learning E Jang, A Irpan, M Khansari, D Kappler, F Ebert, C Lynch, S Levine, ... Conference on Robot Learning, 991-1002, 2022 | 460 | 2022 |
| Learning latent plans from play C Lynch, M Khansari, T Xiao, V Kumar, J Tompson, S Levine, P Sermanet Conference on robot learning, 1113-1132, 2020 | 420 | 2020 |
| Relay policy learning: Solving long-horizon tasks via imitation and reinforcement learning A Gupta, V Kumar, C Lynch, S Levine, K Hausman arXiv preprint arXiv:1910.11956, 2019 | 405 | 2019 |
| Implicit behavioral cloning P Florence, C Lynch, A Zeng, OA Ramirez, A Wahid, L Downs, A Wong, ... Conference on Robot Learning, 158-168, 2022 | 357 | 2022 |
| Language conditioned imitation learning over unstructured data C Lynch, P Sermanet arXiv preprint arXiv:2005.07648, 2020 | 308* | 2020 |
| Interactive language: Talking to robots in real time C Lynch, A Wahid, J Tompson, T Ding, J Betker, R Baruch, T Armstrong, ... IEEE Robotics and Automation Letters, 2023 | 187 | 2023 |
| Wasserstein dependency measure for representation learning S Ozair, C Lynch, Y Bengio, A Van den Oord, S Levine, P Sermanet Advances in Neural Information Processing Systems 32, 2019 | 115 | 2019 |
| Learning actionable representations from visual observations D Dwibedi, J Tompson, C Lynch, P Sermanet 2018 IEEE/RSJ international conference on intelligent robots and systems …, 2018 | 98 | 2018 |
| Images don't lie: Transferring deep visual semantic features to large-scale multimodal learning to rank C Lynch, K Aryafar, J Attenberg Proceedings of the 22nd ACM SIGKDD international conference on knowledge …, 2016 | 76 | 2016 |
| Online object representations with contrastive learning S Pirk, M Khansari, Y Bai, C Lynch, P Sermanet arXiv preprint arXiv:1906.04312, 2019 | 33 | 2019 |
| Broadly-exploring, local-policy trees for long-horizon task planning P Sermanet, C Lynch 5th Annual Conference on Robot Learning, 2021 | 32* | 2021 |
| Bootstrapped autonomous practicing via multi-task reinforcement learning A Gupta, C Lynch, B Kinman, G Peake, S Levine, K Hausman 2023 IEEE International Conference on Robotics and Automation (ICRA), 5020-5026, 2023 | 16 | 2023 |
| Visuomotor control in multi-object scenes using object-aware representations N Heravi, A Wahid, C Lynch, P Florence, T Armstrong, J Tompson, ... 2023 IEEE International Conference on Robotics and Automation (ICRA), 9515-9522, 2023 | 15 | 2023 |
| Goalseye: Learning high speed precision table tennis on a physical robot T Ding, L Graesser, S Abeyruwan, DB D'Ambrosio, A Shankar, ... arXiv preprint arXiv:2210.03662, 2022 | 14* | 2022 |
| Online learning of object representations by appearance space feature alignment S Pirk, M Khansari, Y Bai, C Lynch, P Sermanet 2020 IEEE International Conference on Robotics and Automation (ICRA), 10473 …, 2020 | 13 | 2020 |
| Robotic table tennis: A case study into a high speed learning system DB D'Ambrosio, J Abelian, S Abeyruwan, M Ahn, A Bewley, J Boyd, ... arXiv preprint arXiv:2309.03315, 2023 | 11 | 2023 |
| Learning to play by imitating humans R Dinyari, P Sermanet, C Lynch arXiv preprint arXiv:2006.06874, 2020 | 5 | 2020 |
| Training and/or utilizing machine learning model (s) for use in natural language based robotic control P Sermanet, C Lynch US Patent App. 17/924,891, 2023 | 4 | 2023 |