Sergey Levine

Meta-Learning without Memorization

Mingzhang Yin, George Tucker, Mingyuan Zhou, Sergey Levine, Chelsea Finn

Comments ICLR 2020

Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning

Archit Sharma, Michael Ahn, Sergey Levine, Vikash Kumar, Karol Hausman, Shixiang Gu

The Ingredients of Real-World Robotic Reinforcement Learning

Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, Sergey Levine

Comments First three authors contributed equally. Accepted as a spotlight presentation at ICLR 2020

Thinking While Moving: Deep Reinforcement Learning with Concurrent Control

Ted Xiao, Eric Jang, Dmitry Kalashnikov, Sergey Levine, Julian Ibarz, Karol Hausman, Alexander Herzog

Comments Published as a conference paper at ICLR 2020

The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget

Anirudh Goyal, Yoshua Bengio, Matthew Botvinick, Sergey Levine

Comments Published as a conference paper at ICLR 2020

BADGR: An Autonomous Self-Supervised Learning-Based Navigation System

Gregory Kahn, Pieter Abbeel, Sergey Levine

DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction

Aviral Kumar, Abhishek Gupta, Sergey Levine

Comments Pre-print

OmniTact: A Multi-Directional High Resolution Touch Sensor

Akhil Padmanabha, Frederik Ebert, Stephen Tian, Roberto Calandra, Chelsea Finn, Sergey Levine

Comments Accepted at International Conference on Robotics and Automation (ICRA) 2020

Scaled Autonomy: Enabling Human Operators to Control Robot Fleets

Gokul Swamy, Siddharth Reddy, Sergey Levine, Anca D. Dragan

Comments Accepted to International Conference on Robotics and Automation (ICRA) 2020

Scalable Multi-Task Imitation Learning with Autonomous Improvement

Avi Singh, Eric Jang, Alexander Irpan, Daniel Kappler, Murtaza Dalal, Sergey Levine, Mohi Khansari, Chelsea Finn

Comments Accepted to ICRA 2020. Supplementary material at https://sites.google.com/view/scalable-mili

Efficient Exploration via State Marginal Matching

Lisa Lee, Benjamin Eysenbach, Emilio Parisotto, Eric Xing, Sergey Levine, Ruslan Salakhutdinov

Comments Videos and code: https://sites.google.com/view/state-marginal-matching

Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement

Benjamin Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov

Temporal Difference Models: Model-Free Deep RL for Model-Based Control

Vitchyr Pong, Shixiang Gu, Murtaza Dalal, Sergey Levine

Comments Appeared in ICLR 2018; typos corrected

Dynamics-Aware Unsupervised Discovery of Skills

Archit Sharma, Shixiang Gu, Sergey Levine, Vikash Kumar, Karol Hausman

Dynamical Distance Learning for Semi-Supervised and Unsupervised Skill Discovery

Kristian Hartikainen, Xinyang Geng, Tuomas Haarnoja, Sergey Levine

Comments 11+6 pages, 6+2 figures, last two authors (Tuomas Haarnoja, Sergey Levine) advised equally

VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation

Manoj Kumar, Mohammad Babaeizadeh, Dumitru Erhan, Chelsea Finn, Sergey Levine, Laurent Dinh, Durk Kingma

Comments ICLR 2020 Camera-Ready. Previous title: VideoFlow: A Flow-Based Generative Model for Video

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

RoboNet: Large-Scale Multi-Robot Learning

Sudeep Dasari, Frederik Ebert, Stephen Tian, Suraj Nair, Bernadette Bucher, Karl Schmeckpeper, Siddharth Singh, Sergey Levine, Chelsea Finn

Comments accepted at the Conference on Robot Learning (CoRL) 2019

Reward-Conditioned Policies

Aviral Kumar, Xue Bin Peng, Sergey Levine

Model Inversion Networks for Model-Based Optimization

Aviral Kumar, Sergey Levine

Morphology-Agnostic Visual Robotic Control

Brian Yang, Dinesh Jayaraman, Glen Berseth, Alexei Efros, Sergey Levine

Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?

Ofir Nachum, Haoran Tang, Xingyu Lu, Shixiang Gu, Honglak Lee, Sergey Levine

Comments Presented as an oral at the NeurIPS 2019 DeepRL Workshop

Learning Predictive Models From Observation and Interaction

Karl Schmeckpeper, Annie Xie, Oleh Rybkin, Stephen Tian, Kostas Daniilidis, Sergey Levine, Chelsea Finn

Learning Latent Plans from Play

Corey Lynch, Mohi Khansari, Ted Xiao, Vikash Kumar, Jonathan Tompson, Sergey Levine, Pierre Sermanet

Comments Published at CoRL 2019 (3rd Conference on Robot Learning, Osaka, Japan)

ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots

Michael Ahn, Henry Zhu, Kristian Hartikainen, Hugo Ponte, Abhishek Gupta, Sergey Levine, Vikash Kumar

Comments Published @ CoRL2019. For details visit - http://www.roboticsbenchmarks.org

Journal ref Conference on Robot Learning, 2019

Unsupervised Curricula for Visual Meta-Reinforcement Learning

Allan Jabri, Kyle Hsu, Ben Eysenbach, Abhishek Gupta, Sergey Levine, Chelsea Finn

Comments NeurIPS 2019

Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction

Aviral Kumar, Justin Fu, George Tucker, Sergey Levine

Comments Accepted at NeurIPS 2019; Project Website: https://sites.google.com/view/bear-off-policyrl

Off-Policy Evaluation via Off-Policy Classification

Alex Irpan, Kanishka Rao, Konstantinos Bousmalis, Chris Harris, Julian Ibarz, Sergey Levine

Comments Accepted to NeurIPS 2019. Camera ready version

Planning with Goal-Conditioned Policies

Soroush Nasiriany, Vitchyr H. Pong, Steven Lin, Sergey Levine

Comments In Advances in Neural Information Processing Systems, 2019

Causal Confusion in Imitation Learning

Pim de Haan, Dinesh Jayaraman, Sergey Levine

Comments Published at NeurIPS 2019 9 pages, plus references and appendices