Marvin Zhang

According to our database, Marvin Zhang authored at least 15 papers between 2015 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

MEMO: Test Time Robustness via Adaptation and Augmentation.

Marvin Zhang, Sergey Levine, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Adaptation Based Approaches to Distribution Shift Problems

Marvin Zhang

PhD thesis, 2021

Adaptive Risk Minimization: Learning to Adapt to Domain Shift.

Marvin Zhang, Henrik Marklund, Nikita Dhawan, Abhishek Gupta, Sergey Levine, Chelsea Finn

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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, Ian Stavness, Wei Guo, Berton Earnshaw, Imran S. Haque, Sara M. Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang

Proceedings of the 38th International Conference on Machine Learning, 2021

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, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang

CoRR, 2020

Adaptive Risk Minimization: A Meta-Learning Approach for Tackling Group Shift.

Marvin Zhang, Henrik Marklund, Abhishek Gupta, Sergey Levine, Chelsea Finn

CoRR, 2020

AVID: Learning Multi-Stage Tasks via Pixel-Level Translation of Human Videos.

Laura M. Smith, Nikita Dhawan, Marvin Zhang, Pieter Abbeel, Sergey Levine

Proceedings of the Robotics: Science and Systems XVI, 2020

2019

When to Trust Your Model: Model-Based Policy Optimization.

Michael Janner, Justin Fu, Marvin Zhang, Sergey Levine

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning.

Marvin Zhang, Sharad Vikram, Laura M. Smith, Pieter Abbeel, Matthew J. Johnson, Sergey Levine

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

SOLAR: Deep Structured Latent Representations for Model-Based Reinforcement Learning.

Marvin Zhang, Sharad Vikram, Laura M. Smith, Pieter Abbeel, Matthew J. Johnson, Sergey Levine

CoRR, 2018

2017

Deep reinforcement learning for tensegrity robot locomotion.

Marvin Zhang, Xinyang Geng, Jonathan Bruce, Ken Caluwaerts, Massimo Vespignani, Vytas SunSpiral, Pieter Abbeel, Sergey Levine

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

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

Proceedings of the 34th International Conference on Machine Learning, 2017

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, Kevin Wayne

Proceedings of the 47th ACM Technical Symposium on Computing Science Education, 2016

Learning deep neural network policies with continuous memory states.

Marvin Zhang, Zoe McCarthy, Chelsea Finn, Sergey Levine, Pieter Abbeel

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

2015

Policy Learning with Continuous Memory States for Partially Observed Robotic Control.

Marvin Zhang, Sergey Levine, Zoe McCarthy, Chelsea Finn, Pieter Abbeel

CoRR, 2015