Papers

My publications and preprints. See also Google Scholar.

*Denotes equal contribution.

  1. Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws
    Yiding Jiang*, Allan Zhou*, Zhili Feng, Sadhika Malladi, J. Zico Kolter.
    Preprint. [arXiv] [Code]
  2. Universal Neural Functionals
    Allan Zhou, Chelsea Finn, James Harrison.
    NeurIPS 2024. [arXiv] [Code]
  3. Neural Processing of Tri-Plane Hybrid Neural Fields
    Adriano Cardace, Pierluigi Zama Ramirez, Francesco Ballerini, Allan Zhou, Samuele Salti, Luigi Di Stefano.
    ICLR 2024. [arXiv]
  4. Fleet Policy Learning via Weight Merging and An Application to Robotic Tool-Use
    Lirui Wang, Kaiqing Zhang, Allan Zhou, Max Simchowitz, Russ Tedrake.
    ICLR 2024. [arXiv]
  5. Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning
    Evan Zheran Liu, Sahaana Suri, Tong Mu, Allan Zhou, Chelsea Finn.
    ICML 2023. [arXiv]
  6. 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. [arXiv]
  7. Neural Functional Transformers
    Allan Zhou, Kaien Yang, Yiding Jiang, Kaylee Burns, Winnie Xu, Samuel Sokota, J. Zico Kolter, Chelsea Finn.
    NeurIPS 2023. [arXiv]
  8. Permutation Equivariant Neural Functionals
    Allan Zhou, Kaien Yang, Kaylee Burns, Adriano Cardace, Yiding Jiang, Samuel Sokota, J. Zico Kolter, Chelsea Finn.
    NeurIPS 2023. [arXiv] [Code]
  9. 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. [arXiv][Videos]
  10. Unsupervised language models for disease variant prediction
    Allan Zhou*, Nicholas C. Landolfi*, Daniel C. O’Neill.
    ML for Structural Biology and Learning Meaningful Representation of Life (Spotlight) Workshops, NeurIPS 2022. [arXiv][Spotlight video]
  11. Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations
    Huaxiu Yao*, Xinyu Yang*, Allan Zhou, Chelsea Finn.
    Distribution Shift Workshop, NeurIPS 2022. [arXiv]
  12. Policy Architectures for Compositional Generalization in Control
    Allan Zhou, Vikash Kumar, Chelsea Finn, Aravind Rajeswaran.
    Reinforcement Learning Conference (RLC) 2024. [arXiv][Site][Code]
  13. Do deep networks transfer invariances across classes?
    Allan Zhou*, Fahim Tajwar*, Alexander Robey, Tom Knowles, George J. Pappas, Hamed Hassani, Chelsea Finn.
    ICLR 2022. [arXiv][Code]
  14. Noether Networks: meta-learning useful conserved quantities
    Ferran Alet*, Dylan Doblar*, Allan Zhou, Joshua B. Tenenbaum, Kenji Kawaguchi, Chelsea Finn.
    NeurIPS 2021. [arXiv][Site][Code]
  15. Discriminator Augmented Model-based Reinforcement Learning
    Behzad Haghgoo*, Allan Zhou*, Archit Sharma, Chelsea Finn.
    NeurIPS 2021 Deep RL Workshop. [arXiv]
  16. Meta-Learning Symmetries by Reparameterization
    Allan Zhou, Tom Knowles, Chelsea Finn.
    ICLR 2021. [arXiv][Code]
  17. Watch, Try, Learn: Meta-Learning from Demonstrations and Reward
    Allan Zhou, Eric Jang, Daniel Kappler, Alex Herzog, Mohi Khansari, Paul Wohlhart, Yunfei Bai, Mrinal Kalakrishnan, Sergey Levine, Chelsea Finn.
    ICLR 2020. [arXiv]
  18. Cost functions for robot motion style
    Allan Zhou, Anca Dragan.
    IROS 2018. [arXiv]
  19. Expressive Robot Motion Timing
    Allan Zhou, Dylan Hadfield-Menell, Anusha Nagabandi, Anca Dragan.
    HRI 2017. [arXiv]