Get our free extension to see links to code for papers anywhere online!

 Add to Chrome

 Add to Firefox

 CatalyzeX Code Finder - Browser extension linking code for ML papers across the web! | Product Hunt Embed
Sergey Levine
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning

Oct 27, 2020
Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum

* https://sites.google.com/view/opal-iclr 
  Access Paper or Ask Questions
LaND: Learning to Navigate from Disengagements

Oct 09, 2020
Gregory Kahn, Pieter Abbeel, Sergey Levine


  Access Paper or Ask Questions
Multi-agent Social Reinforcement Learning Improves Generalization

Oct 01, 2020
Kamal Ndousse, Douglas Eck, Sergey Levine, Natasha Jaques

* 12 pages, 11 figures 
  Access Paper or Ask Questions
Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings

Aug 15, 2020
Jesse Zhang, Brian Cheung, Chelsea Finn, Sergey Levine, Dinesh Jayaraman

* 15 pages, 8 figures, ICML 2020. Website with code: https://sites.google.com/berkeley.edu/carl 
  Access Paper or Ask Questions
Offline Meta-Reinforcement Learning with Advantage Weighting

Aug 13, 2020
Eric Mitchell, Rafael Rafailov, Xue Bin Peng, Sergey Levine, Chelsea Finn

* 8 pages main text; 18 pages total 
  Access Paper or Ask Questions
Assisted Perception: Optimizing Observations to Communicate State

Aug 06, 2020
Siddharth Reddy, Sergey Levine, Anca D. Dragan


  Access Paper or Ask Questions
Adaptive Risk Minimization: A Meta-Learning Approach for Tackling Group Shift

Jul 06, 2020
Marvin Zhang, Henrik Marklund, Abhishek Gupta, Sergey Levine, Chelsea Finn

* Project website: https://sites.google.com/view/adaptive-risk-minimization ; Code: https://github.com/henrikmarklund/arm 
  Access Paper or Ask Questions
Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions

Jul 05, 2020
Michael Chang, Sidhant Kaushik, S. Matthew Weinberg, Thomas L. Griffiths, Sergey Levine

* 17 pages, 12 figures, accepted to the International Conference on Machine Learning (ICML) 2020 
  Access Paper or Ask Questions
Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems

Jun 30, 2020
Anirudh Goyal, Alex Lamb, Phanideep Gampa, Philippe Beaudoin, Sergey Levine, Charles Blundell, Yoshua Bengio, Michael Mozer

* Under Review, NeurIPS 2020 
  Access Paper or Ask Questions
Conservative Q-Learning for Offline Reinforcement Learning

Jun 29, 2020
Aviral Kumar, Aurick Zhou, George Tucker, Sergey Levine

* Preprint. Website at: https://sites.google.com/view/cql-offline-rl 
  Access Paper or Ask Questions
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts?

Jun 26, 2020
Angelos Filos, Panagiotis Tigas, Rowan McAllister, Nicholas Rhinehart, Sergey Levine, Yarin Gal

* Camera-ready version, International Conference of Machine Learning 2020 
  Access Paper or Ask Questions
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers

Jun 24, 2020
Benjamin Eysenbach, Swapnil Asawa, Shreyas Chaudhari, Ruslan Salakhutdinov, Sergey Levine


  Access Paper or Ask Questions
Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors

Jun 23, 2020
Karl Pertsch, Oleh Rybkin, Frederik Ebert, Chelsea Finn, Dinesh Jayaraman, Sergey Levine

* Project page: orybkin.github.io/video-gcp 
  Access Paper or Ask Questions
Simple and Effective VAE Training with Calibrated Decoders

Jun 23, 2020
Oleh Rybkin, Kostas Daniilidis, Sergey Levine

* Project website: \url{https://orybkin.github.io/sigma-vae/} 
  Access Paper or Ask Questions
Ecological Reinforcement Learning

Jun 22, 2020
John D. Co-Reyes, Suvansh Sanjeev, Glen Berseth, Abhishek Gupta, Sergey Levine

* Preprint. Website at: https://sites.google.com/view/ecological-rl/home 
  Access Paper or Ask Questions
Learning Invariant Representations for Reinforcement Learning without Reconstruction

Jun 18, 2020
Amy Zhang, Rowan McAllister, Roberto Calandra, Yarin Gal, Sergey Levine


  Access Paper or Ask Questions
Accelerating Online Reinforcement Learning with Offline Datasets

Jun 16, 2020
Ashvin Nair, Murtaza Dalal, Abhishek Gupta, Sergey Levine

* 16 pages. Website: https://awacrl.github.io/ 
  Access Paper or Ask Questions
RL-CycleGAN: Reinforcement Learning Aware Simulation-To-Real

Jun 16, 2020
Kanishka Rao, Chris Harris, Alex Irpan, Sergey Levine, Julian Ibarz, Mohi Khansari

* Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2020) 
  Access Paper or Ask Questions
Meta-Reinforcement Learning Robust to Distributional Shift via Model Identification and Experience Relabeling

Jun 15, 2020
Russell Mendonca, Xinyang Geng, Chelsea Finn, Sergey Levine


  Access Paper or Ask Questions
MOPO: Model-based Offline Policy Optimization

May 27, 2020
Tianhe Yu, Garrett Thomas, Lantao Yu, Stefano Ermon, James Zou, Sergey Levine, Chelsea Finn, Tengyu Ma

* First two authors contributed equally. Last two authors advised equally 
  Access Paper or Ask Questions
Meta-Reinforcement Learning for Robotic Industrial Insertion Tasks

May 23, 2020
Gerrit Schoettler, Ashvin Nair, Juan Aparicio Ojea, Sergey Levine, Eugen Solowjow

* 9 pages, 8 figures 
  Access Paper or Ask Questions
Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

May 04, 2020
Sergey Levine, Aviral Kumar, George Tucker, Justin Fu


  Access Paper or Ask Questions
Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning

Apr 27, 2020
Archit Sharma, Michael Ahn, Sergey Levine, Vikash Kumar, Karol Hausman, Shixiang Gu


  Access Paper or Ask Questions
The Ingredients of Real-World Robotic Reinforcement Learning

Apr 27, 2020
Henry Zhu, Justin Yu, Abhishek Gupta, Dhruv Shah, Kristian Hartikainen, Avi Singh, Vikash Kumar, Sergey Levine

* First three authors contributed equally. Accepted as a spotlight presentation at ICLR 2020 
  Access Paper or Ask Questions
Thinking While Moving: Deep Reinforcement Learning with Concurrent Control

Apr 25, 2020
Ted Xiao, Eric Jang, Dmitry Kalashnikov, Sergey Levine, Julian Ibarz, Karol Hausman, Alexander Herzog

* Published as a conference paper at ICLR 2020 
  Access Paper or Ask Questions
The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget

Apr 24, 2020
Anirudh Goyal, Yoshua Bengio, Matthew Botvinick, Sergey Levine

* Published as a conference paper at ICLR 2020 
  Access Paper or Ask Questions