Benjamin Eysenbach - researchr alias

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Viewing Publication 1 - 27 from 27

2023

A Connection between One-Step RL and Critic Regularization in Reinforcement LearningBenjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov. icml 2023: 9485-9507 [doi]

Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One ObjectiveRaj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Russ Salakhutdinov. iclr 2023: [doi]

Contrastive Example-Based ControlKyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn. l4dc 2023: 155-169 [doi]

Contrastive Value Learning: Implicit Models for Simple Offline RLBogdan Mazoure, Benjamin Eysenbach, Ofir Nachum, Jonathan Tompson. corl 2023: 1257-1267 [doi]

When Do Transformers Shine in RL? Decoupling Memory from Credit AssignmentTianwei Ni, Michel Ma, Benjamin Eysenbach, Pierre-Luc Bacon. nips 2023: [doi]

HIQL: Offline Goal-Conditioned RL with Latent States as ActionsSeohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine. nips 2023: [doi]

Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group ShiftsAmrith Setlur, Don Kurian Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine. iclr 2023: [doi]

2022

RvS: What is Essential for Offline RL via Supervised Learning?Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine. iclr 2022: [doi]

Mismatched No More: Joint Model-Policy Optimization for Model-Based RLBenjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov. nips 2022: [doi]

Maximum Entropy RL (Provably) Solves Some Robust RL ProblemsBenjamin Eysenbach, Sergey Levine. iclr 2022: [doi]

The Information Geometry of Unsupervised Reinforcement LearningBenjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine. iclr 2022: [doi]

Contrastive Learning as Goal-Conditioned Reinforcement LearningBenjamin Eysenbach, Tianjun Zhang, Sergey Levine, Ruslan Salakhutdinov. nips 2022: [doi]

Imitating Past Successes can be Very SuboptimalBenjamin Eysenbach, Soumith Udatha, Russ Salakhutdinov, Sergey Levine. nips 2022: [doi]

Learning Options via CompressionYiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, J. Zico Kolter, Chelsea Finn. nips 2022: [doi]

Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPsTianwei Ni, Benjamin Eysenbach, Ruslan Salakhutdinov. icml 2022: 16691-16723 [doi]

Adversarial Unlearning: Reducing Confidence Along Adversarial DirectionsAmrith Setlur, Benjamin Eysenbach, Virginia Smith, Sergey Levine. nips 2022: [doi]

C-Planning: An Automatic Curriculum for Learning Goal-Reaching TasksTianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez. iclr 2022: [doi]

2021

Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic SkillsYevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jacob Varley, Alex Irpan, Benjamin Eysenbach, Ryan Julian, Chelsea Finn, Sergey Levine. icml 2021: 1518-1528 [doi]

Off-Dynamics Reinforcement Learning: Training for Transfer with Domain ClassifiersBenjamin Eysenbach, Shreyas Chaudhari, Swapnil Asawa, Sergey Levine, Ruslan Salakhutdinov. iclr 2021: [doi]

C-Learning: Learning to Achieve Goals via Recursive ClassificationBenjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine. iclr 2021: [doi]

Learning to Reach Goals via Iterated Supervised LearningDibya Ghosh, Abhishek Gupta 0004, Ashwin Reddy, Justin Fu, Coline Manon Devin, Benjamin Eysenbach, Sergey Levine. iclr 2021: [doi]

ViNG: Learning Open-World Navigation with Visual GoalsDhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, Sergey Levine. icra 2021: 13215-13222 [doi]

Rapid Exploration for Open-World Navigation with Latent Goal ModelsDhruv Shah, Benjamin Eysenbach, Nicholas Rhinehart, Sergey Levine. corl 2021: 674-684 [doi]

Model-Based Visual Planning with Self-Supervised Functional DistancesStephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Benjamin Eysenbach, Chelsea Finn, Sergey Levine. iclr 2021: [doi]

2019

Diversity is All You Need: Learning Skills without a Reward FunctionBenjamin Eysenbach, Abhishek Gupta 0004, Julian Ibarz, Sergey Levine. iclr 2019: [doi]

2018

Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory EmbeddingsJohn D. Co-Reyes, Yuxuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine. icml 2018: 1008-1017 [doi]

Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement LearningBenjamin Eysenbach, Shixiang Gu, Julian Ibarz, Sergey Levine. iclr 2018: [doi]

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