Lee, Alex X.

Stochastic latent actor–critic: Deep reinforcement learning with a latent variable model

Lee, A. X., Nagabandi, A., Abbeel, P., & Levine, S. (2019) · arXiv

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 159

Learning force-based manipulation of deformable objects from multiple demonstrations

Lee, A. X., Lu, H., Gupta, A., Levine, S., & Abbeel, P. (2015) · 2015 IEEE International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 140

Unifying scene registration and trajectory optimization for learning from demonstrations with application to manipulation of deformable objects

Lee, A. X., Huang, S. H., Hadfield-Menell, D., Tzeng, E., & Abbeel, P. (2014) · 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 32

RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation

Bousmalis, K., Vezzani, G., Rao, D., Devin, C., Lee, A. X., Bauza, M., Davchev, T., Zhou, Y., Gupta, A., Raju, A., et al. (2023) · arXiv

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 13

A non-rigid point and normal registration algorithm with applications to learning from demonstrations

Lee, A. X., Goldstein, M. A., Barratt, S. T., & Abbeel, P. (2015) · 2015 IEEE International Conference on Robotics and Automation (ICRA)

Robot Manipulation and LearningReinforcement Learning in Robotics

Cited by 12

Gemini Robotics: Bringing AI into the Physical World

Gemini Robotics Team, Abeyruwan, S., Ainslie, J., Alayrac, J.-B., Arenas, M. G., Armstrong, T., Balakrishna, A., Baruch, R., Bauza, M., Blokzijl, M., et al. (2025) · arXiv

Robot Manipulation and LearningMultimodal Machine Learning Applications

Cited by 8