Zhou, Aurick

8 publications

ICCV 2023 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

ICML 2021 Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation Aurick Zhou, Sergey Levine

NeurIPS 2021 Bayesian Adaptation for Covariate Shift Aurick Zhou, Sergey Levine

ICML 2021 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

NeurIPS 2020 Conservative Q-Learning for Offline Reinforcement Learning Aviral Kumar, Aurick Zhou, George Tucker, Sergey Levine

ICML 2019 Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables Kate Rakelly, Aurick Zhou, Chelsea Finn, Sergey Levine, Deirdre Quillen

ICLRW 2019 Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables Kate Rakelly, Aurick Zhou, Deirdre Quillen, Chelsea Finn, Sergey Levine

ICML 2018 Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, Sergey Levine