Policy Learning with Continuous Memory States for Partially Observed Robotic Control. - Marvin Zhang; Sergey Levine; Zoe McCarthy; Chelsea Finn; Pieter Abbeel (CoRR, 2015)

Learning deep neural network policies with continuous memory states. - Marvin Zhang; Zoe McCarthy; Chelsea Finn; Sergey Levine; Pieter Abbeel (ICRA, 2016)

Nifty Assignments. - Nick Parlante; Julie Zelenski; Baker Franke; Arvind Bhusnurmath; Karen Her; Kristen Gee; Eric D. Manley; Timothy Urness; Marvin Zhang; Brian Hou; John DeNero; Josh Hug; et al. (SIGCSE, 2016)

Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning. - Yevgen Chebotar; Karol Hausman; Marvin Zhang; Gaurav S. Sukhatme; Stefan Schaal; Sergey Levine (ICML, 2017)

Deep reinforcement learning for tensegrity robot locomotion. - Marvin Zhang; Xinyang Geng; Jonathan Bruce; Ken Caluwaerts; Massimo Vespignani; Vytas SunSpiral; Pieter Abbeel; Sergey Levine (ICRA, 2017)

SOLAR: Deep Structured Latent Representations for Model-Based Reinforcement Learning. - Marvin Zhang; Sharad Vikram; Laura M. Smith; Pieter Abbeel; Matthew J. Johnson 002; Sergey Levine (CoRR, 2018)

SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning. - Marvin Zhang; Sharad Vikram; Laura M. Smith; Pieter Abbeel; Matthew J. Johnson 002; Sergey Levine (ICML, 2019)

When to Trust Your Model: Model-Based Policy Optimization. - Michael Janner; Justin Fu; Marvin Zhang; Sergey Levine (NeurIPS, 2019)

AVID: Learning Multi-Stage Tasks via Pixel-Level Translation of Human Videos. - Laura M. Smith; Nikita Dhawan; Marvin Zhang; Pieter Abbeel; Sergey Levine (Robotics: Science and Systems, 2020)

Adaptive Risk Minimization: A Meta-Learning Approach for Tackling Group Shift. - Marvin Zhang; Henrik Marklund; Abhishek Gupta 004; Sergey Levine; Chelsea Finn (CoRR, 2020)

WILDS: A Benchmark of in-the-Wild Distribution Shifts. - Pang Wei Koh; Shiori Sagawa; Henrik Marklund; Sang Michael Xie; Marvin Zhang; Akshay Balsubramani; Weihua Hu; Michihiro Yasunaga; Richard Lanas Phillips; Sara Beery; Jure Leskovec; Anshul Kundaje; et al. (CoRR, 2020)

WILDS: A Benchmark of in-the-Wild Distribution Shifts. - Pang Wei Koh; Shiori Sagawa; Henrik Marklund; Sang Michael Xie; Marvin Zhang; Akshay Balsubramani; Weihua Hu; Michihiro Yasunaga; Richard Lanas Phillips; Irena Gao; Tony Lee; Etienne David; et al. (ICML, 2021)

Adaptive Risk Minimization: Learning to Adapt to Domain Shift. - Marvin Zhang; Henrik Marklund; Nikita Dhawan; Abhishek Gupta 004; Sergey Levine; Chelsea Finn (NeurIPS, 2021)

Adaptation Based Approaches to Distribution Shift Problems - Marvin Zhang (2021)

MEMO: Test Time Robustness via Adaptation and Augmentation. - Marvin Zhang; Sergey Levine; Chelsea Finn (NeurIPS, 2022)