Expressive Robot Motion Timing. - Allan Zhou; Dylan Hadfield-Menell; Anusha Nagabandi; Anca D. Dragan (HRI, 2017)

Cost Functions for Robot Motion Style. - Allan Zhou; Anca D. Dragan (IROS, 2018)

Watch, Try, Learn: Meta-Learning from Demonstrations and Reward. - Allan Zhou; Eric Jang; Daniel Kappler; Alexander Herzog; Mohi Khansari; Paul Wohlhart; Yunfei Bai; Mrinal Kalakrishnan; Sergey Levine; Chelsea Finn (CoRR, 2019)

Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards. - Allan Zhou; Eric Jang; Daniel Kappler; Alexander Herzog; Mohi Khansari; Paul Wohlhart; Yunfei Bai; Mrinal Kalakrishnan; Sergey Levine; Chelsea Finn (ICLR, 2020)

Meta-learning Symmetries by Reparameterization. - Allan Zhou; Tom Knowles; Chelsea Finn (ICLR, 2021)

Noether Networks: meta-learning useful conserved quantities. - Ferran Alet; Dylan Doblar; Allan Zhou; Josh Tenenbaum 001; Kenji Kawaguchi; Chelsea Finn (NeurIPS, 2021)

Discriminator Augmented Model-Based Reinforcement Learning. - Behzad Haghgoo; Allan Zhou; Archit Sharma; Chelsea Finn (CoRR, 2021)

Do deep networks transfer invariances across classes? - Allan Zhou; Fahim Tajwar; Alexander Robey; Tom Knowles; George J. Pappas; Hamed Hassani; Chelsea Finn (ICLR, 2022)

Unsupervised language models for disease variant prediction. - Allan Zhou; Nicholas C. Landolfi; Daniel C. O'Neill (CoRR, 2022)

NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesis. - Allan Zhou; Moo Jin Kim; Lirui Wang; Pete Florence; Chelsea Finn (CVPR, 2023)

Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback. - Katherine Tian; Eric Mitchell; Allan Zhou; Archit Sharma; Rafael Rafailov; Huaxiu Yao; Chelsea Finn; Christopher D. Manning (EMNLP, 2023)

Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning. - Evan Zheran Liu; Sahaana Suri; Tong Mu; Allan Zhou; Chelsea Finn (ICML, 2023)

Permutation Equivariant Neural Functionals. - Allan Zhou; Kaien Yang; Kaylee Burns; Adriano Cardace; Yiding Jiang; Samuel Sokota; J. Zico Kolter; Chelsea Finn (NeurIPS, 2023)

Neural Functional Transformers. - Allan Zhou; Kaien Yang; Yiding Jiang; Kaylee Burns; Winnie Xu; Samuel Sokota; J. Zico Kolter; Chelsea Finn (NeurIPS, 2023)

Permutation Equivariant Neural Functionals. - Allan Zhou; Kaien Yang; Kaylee Burns; Yiding Jiang; Samuel Sokota; J. Zico Kolter; Chelsea Finn (CoRR, 2023)

Fleet Policy Learning via Weight Merging and An Application to Robotic Tool-Use. - Lirui Wang; Kaiqing Zhang; Allan Zhou; Max Simchowitz; Russ Tedrake (CoRR, 2023)

Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations. - Xinyu Yang 002; Huaxiu Yao; Allan Zhou; Chelsea Finn (Trans. Mach. Learn. Res., 2023)

Neural Processing of Tri-Plane Hybrid Neural Fields. - Adriano Cardace; Pierluigi Zama Ramirez; Francesco Ballerini; Allan Zhou; Samuele Salti; Luigi Di Stefano (ICLR, 2024)

Robot Fleet Learning via Policy Merging. - Lirui Wang; Kaiqing Zhang; Allan Zhou; Max Simchowitz; Russ Tedrake (ICLR, 2024)

Universal Neural Functionals. - Allan Zhou; Chelsea Finn; James Harrison (NeurIPS, 2024)

Policy Architectures for Compositional Generalization in Control. - Allan Zhou; Vikash Kumar; Chelsea Finn; Aravind Rajeswaran (RLJ, 2024)

AutoFT: Robust Fine-Tuning by Optimizing Hyperparameters on OOD Data. - Caroline Choi; Yoonho Lee 001; Annie S. Chen; Allan Zhou; Aditi Raghunathan; Chelsea Finn (CoRR, 2024)

Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws. - Yiding Jiang; Allan Zhou; Zhili Feng; Sadhika Malladi; J. Zico Kolter (ICLR, 2025)