| 2023 | ICCV | MotionLM: Multi-Agent Motion Forecasting as Language Modeling. | Ari Seff, Brian Cera, Dian Chen, Mason Ng, Aurick Zhou, Nigamaa Nayakanti, Khaled S. Refaat, Rami Al-Rfou, Benjamin Sapp |
| 2023 | ICRA | Wayformer: Motion Forecasting via Simple & Efficient Attention Networks. | Nigamaa Nayakanti, Rami Al-Rfou, Aurick Zhou, Kratarth Goel, Khaled S. Refaat, Benjamin Sapp |
| 2021 | ICML | MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning. | Kevin Li, Abhishek Gupta, Ashwin Reddy, Vitchyr H. Pong, Aurick Zhou, Justin Yu, Sergey Levine |
| 2021 | ICML | Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation. | Aurick Zhou, Sergey Levine |
| 2019 | ICML | Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables. | Kate Rakelly, Aurick Zhou, Chelsea Finn, Sergey Levine, Deirdre Quillen |
| 2018 | ICML | Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor. | Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, Sergey Levine |
| 2018 | ICRA | Composable Deep Reinforcement Learning for Robotic Manipulation. | Tuomas Haarnoja, Vitchyr Pong, Aurick Zhou, Murtaza Dalal, Pieter Abbeel, Sergey Levine |