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2020 – today
- 2024
[c41]Raj Ghugare, Matthieu Geist, Glen Berseth, Benjamin Eysenbach:
Closing the Gap between TD Learning and Supervised Learning - A Generalisation Point of View. ICLR 2024- [c40]Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Xiangyu Liu, Benjamin Eysenbach, Tuomas Sandholm, Furong Huang, Stephen Marcus McAleer:
Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations. ICLR 2024 - [c39]Tianwei Ni, Benjamin Eysenbach, Erfan Seyedsalehi, Michel Ma, Clement Gehring, Aditya Mahajan, Pierre-Luc Bacon:
Bridging State and History Representations: Understanding Self-Predictive RL. ICLR 2024 - [c38]Chongyi Zheng, Benjamin Eysenbach, Homer Rich Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine:
Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data. ICLR 2024 - [c37]Chongyi Zheng, Ruslan Salakhutdinov, Benjamin Eysenbach:
Contrastive Difference Predictive Coding. ICLR 2024 - [c36]Ifigeneia Apostolopoulou, Benjamin Eysenbach, Frank Nielsen, Artur Dubrawski:
A Rate-Distortion View of Uncertainty Quantification. ICML 2024 - [c35]Vivek Myers, Chongyi Zheng, Anca D. Dragan, Sergey Levine, Benjamin Eysenbach:
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making. ICML 2024 - [i51]Tianwei Ni, Benjamin Eysenbach
, Erfan Seyedsalehi, Michel Ma, Clement Gehring, Aditya Mahajan, Pierre-Luc Bacon:
Bridging State and History Representations: Understanding Self-Predictive RL. CoRR abs/2401.08898 (2024) - [i50]Raj Ghugare, Matthieu Geist, Glen Berseth, Benjamin Eysenbach:
Closing the Gap between TD Learning and Supervised Learning - A Generalisation Point of View. CoRR abs/2401.11237 (2024) - [i49]Benjamin Eysenbach, Vivek Myers, Ruslan Salakhutdinov, Sergey Levine:
Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference. CoRR abs/2403.04082 (2024) - [i48]Ifigeneia Apostolopoulou, Benjamin Eysenbach, Frank Nielsen, Artur Dubrawski:
A Rate-Distortion View of Uncertainty Quantification. CoRR abs/2406.10775 (2024) - [i47]Vivek Myers, Chongyi Zheng, Anca D. Dragan, Sergey Levine, Benjamin Eysenbach:
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making. CoRR abs/2406.17098 (2024) - [i46]Grace Liu, Michael Tang, Benjamin Eysenbach:
A Single Goal is All You Need: Skills and Exploration Emerge from Contrastive RL without Rewards, Demonstrations, or Subgoals. CoRR abs/2408.05804 (2024) - [i45]Michal Bortkiewicz, Wladek Palucki, Vivek Myers, Tadeusz Dziarmaga, Tomasz Arczewski, Lukasz Kucinski, Benjamin Eysenbach:
Accelerating Goal-Conditioned RL Algorithms and Research. CoRR abs/2408.11052 (2024) - [i44]Kyle Beltran Hatch, Ashwin Balakrishna, Oier Mees, Suraj Nair, Seohong Park, Blake Wulfe, Masha Itkina, Benjamin Eysenbach, Sergey Levine, Thomas Kollar, Benjamin Burchfiel:
GHIL-Glue: Hierarchical Control with Filtered Subgoal Images. CoRR abs/2410.20018 (2024) - [i43]Seohong Park, Kevin Frans, Benjamin Eysenbach, Sergey Levine:
OGBench: Benchmarking Offline Goal-Conditioned RL. CoRR abs/2410.20092 (2024) - 2023
- [c34]Bogdan Mazoure, Benjamin Eysenbach, Ofir Nachum, Jonathan Tompson:
Contrastive Value Learning: Implicit Models for Simple Offline RL. CoRL 2023: 1257-1267 - [c33]Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Russ Salakhutdinov:
Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective. ICLR 2023 - [c32]Amrith Setlur, Don Kurian Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine:
Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts. ICLR 2023 - [c31]Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov:
A Connection between One-Step RL and Critic Regularization in Reinforcement Learning. ICML 2023: 9485-9507 - [c30]Kyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn:
Contrastive Example-Based Control. L4DC 2023: 155-169 - [c29]Tianwei Ni, Michel Ma, Benjamin Eysenbach, Pierre-Luc Bacon:
When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment. NeurIPS 2023 - [c28]Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine:
HIQL: Offline Goal-Conditioned RL with Latent States as Actions. NeurIPS 2023 - [i42]Amrith Setlur, Don Kurian Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine:
Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts. CoRR abs/2302.02931 (2023) - [i41]Chongyi Zheng, Benjamin Eysenbach, Homer Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine:
Stabilizing Contrastive RL: Techniques for Offline Goal Reaching. CoRR abs/2306.03346 (2023) - [i40]Tianwei Ni, Michel Ma, Benjamin Eysenbach, Pierre-Luc Bacon:
When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment. CoRR abs/2307.03864 (2023) - [i39]Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine:
HIQL: Offline Goal-Conditioned RL with Latent States as Actions. CoRR abs/2307.11949 (2023) - [i38]Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov:
A Connection between One-Step Regularization and Critic Regularization in Reinforcement Learning. CoRR abs/2307.12968 (2023) - [i37]Kyle Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn:
Contrastive Example-Based Control. CoRR abs/2307.13101 (2023) - [i36]Chongyi Zheng, Ruslan Salakhutdinov, Benjamin Eysenbach:
Contrastive Difference Predictive Coding. CoRR abs/2310.20141 (2023) - 2022
- [c27]Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine:
RvS: What is Essential for Offline RL via Supervised Learning? ICLR 2022 - [c26]Benjamin Eysenbach, Sergey Levine:
Maximum Entropy RL (Provably) Solves Some Robust RL Problems. ICLR 2022 - [c25]Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
The Information Geometry of Unsupervised Reinforcement Learning. ICLR 2022 - [c24]Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez:
C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks. ICLR 2022 - [c23]Tianwei Ni, Benjamin Eysenbach, Ruslan Salakhutdinov:
Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs. ICML 2022: 16691-16723 - [c22]Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov:
Mismatched No More: Joint Model-Policy Optimization for Model-Based RL. NeurIPS 2022 - [c21]Benjamin Eysenbach, Soumith Udatha, Russ Salakhutdinov, Sergey Levine:
Imitating Past Successes can be Very Suboptimal. NeurIPS 2022 - [c20]Benjamin Eysenbach, Tianjun Zhang, Sergey Levine, Ruslan Salakhutdinov:
Contrastive Learning as Goal-Conditioned Reinforcement Learning. NeurIPS 2022 - [c19]Yiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, J. Zico Kolter, Chelsea Finn:
Learning Options via Compression. NeurIPS 2022 - [c18]Amrith Setlur, Benjamin Eysenbach, Virginia Smith, Sergey Levine:
Adversarial Unlearning: Reducing Confidence Along Adversarial Directions. NeurIPS 2022 - [i35]Amrith Setlur, Benjamin Eysenbach, Virginia Smith, Sergey Levine:
Adversarial Unlearning: Reducing Confidence Along Adversarial Directions. CoRR abs/2206.01367 (2022) - [i34]Benjamin Eysenbach, Soumith Udatha, Sergey Levine, Ruslan Salakhutdinov:
Imitating Past Successes can be Very Suboptimal. CoRR abs/2206.03378 (2022) - [i33]Benjamin Eysenbach, Tianjun Zhang, Ruslan Salakhutdinov, Sergey Levine:
Contrastive Learning as Goal-Conditioned Reinforcement Learning. CoRR abs/2206.07568 (2022) - [i32]Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Ruslan Salakhutdinov:
Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective. CoRR abs/2209.08466 (2022) - [i31]Bogdan Mazoure, Benjamin Eysenbach, Ofir Nachum, Jonathan Tompson:
Contrastive Value Learning: Implicit Models for Simple Offline RL. CoRR abs/2211.02100 (2022) - [i30]Yiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, Zico Kolter, Chelsea Finn:
Learning Options via Compression. CoRR abs/2212.04590 (2022) - 2021
- [c17]Dhruv Shah, Benjamin Eysenbach, Nicholas Rhinehart, Sergey Levine:
Rapid Exploration for Open-World Navigation with Latent Goal Models. CoRL 2021: 674-684 - [c16]Benjamin Eysenbach, Shreyas Chaudhari, Swapnil Asawa, Sergey Levine, Ruslan Salakhutdinov:
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers. ICLR 2021 - [c15]Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
C-Learning: Learning to Achieve Goals via Recursive Classification. ICLR 2021 - [c14]Dibya Ghosh, Abhishek Gupta, Ashwin Reddy, Justin Fu, Coline Manon Devin, Benjamin Eysenbach, Sergey Levine:
Learning to Reach Goals via Iterated Supervised Learning. ICLR 2021 - [c13]Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Benjamin Eysenbach, Chelsea Finn, Sergey Levine:
Model-Based Visual Planning with Self-Supervised Functional Distances. ICLR 2021 - [c12]Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jacob Varley, Alex Irpan, Benjamin Eysenbach, Ryan Julian, Chelsea Finn, Sergey Levine:
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills. ICML 2021: 1518-1528 - [c11]Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, Sergey Levine:
ViNG: Learning Open-World Navigation with Visual Goals. ICRA 2021: 13215-13222 - [c10]Ben Eysenbach, Sergey Levine, Ruslan Salakhutdinov:
Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification. NeurIPS 2021: 11541-11552 - [c9]Ben Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
Robust Predictable Control. NeurIPS 2021: 27813-27825 - [i29]Benjamin Eysenbach, Sergey Levine:
Maximum Entropy RL (Provably) Solves Some Robust RL Problems. CoRR abs/2103.06257 (2021) - [i28]Benjamin Eysenbach, Sergey Levine, Ruslan Salakhutdinov:
Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification. CoRR abs/2103.12656 (2021) - [i27]Dhruv Shah, Benjamin Eysenbach, Nicholas Rhinehart, Sergey Levine:
RECON: Rapid Exploration for Open-World Navigation with Latent Goal Models. CoRR abs/2104.05859 (2021) - [i26]Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jake Varley, Alex Irpan, Benjamin Eysenbach, Ryan Julian, Chelsea Finn, Sergey Levine:
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills. CoRR abs/2104.07749 (2021) - [i25]Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
Robust Predictable Control. CoRR abs/2109.03214 (2021) - [i24]Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
The Information Geometry of Unsupervised Reinforcement Learning. CoRR abs/2110.02719 (2021) - [i23]Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov:
Mismatched No More: Joint Model-Policy Optimization for Model-Based RL. CoRR abs/2110.02758 (2021) - [i22]Tianwei Ni, Benjamin Eysenbach, Ruslan Salakhutdinov:
Recurrent Model-Free RL is a Strong Baseline for Many POMDPs. CoRR abs/2110.05038 (2021) - [i21]Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez:
C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks. CoRR abs/2110.12080 (2021) - [i20]Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine:
RvS: What is Essential for Offline RL via Supervised Learning? CoRR abs/2112.10751 (2021) - 2020
- [c8]Tianwei Ni, Harshit S. Sikchi, Yufei Wang, Tejus Gupta, Lisa Lee, Ben Eysenbach:
f-IRL: Inverse Reinforcement Learning via State Marginal Matching. CoRL 2020: 529-551 - [c7]Ben Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov:
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement. NeurIPS 2020 - [c6]Lisa Lee, Ben Eysenbach, Ruslan Salakhutdinov, Shixiang Shane Gu, Chelsea Finn:
Weakly-Supervised Reinforcement Learning for Controllable Behavior. NeurIPS 2020 - [i19]Benjamin Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov:
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement. CoRR abs/2002.11089 (2020) - [i18]Lisa Lee, Benjamin Eysenbach, Ruslan Salakhutdinov, Shixiang Gu, Chelsea Finn:
Weakly-Supervised Reinforcement Learning for Controllable Behavior. CoRR abs/2004.02860 (2020) - [i17]Benjamin Eysenbach, Swapnil Asawa, Shreyas Chaudhari, Ruslan Salakhutdinov, Sergey Levine:
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers. CoRR abs/2006.13916 (2020) - [i16]Shuby Deshpande, Benjamin Eysenbach, Jeff Schneider:
Interactive Visualization for Debugging RL. CoRR abs/2008.07331 (2020) - [i15]Krishnan Srinivasan, Benjamin Eysenbach, Sehoon Ha, Jie Tan, Chelsea Finn:
Learning to be Safe: Deep RL with a Safety Critic. CoRR abs/2010.14603 (2020) - [i14]Tianwei Ni, Harshit S. Sikchi, Yufei Wang, Tejus Gupta, Lisa Lee, Benjamin Eysenbach:
f-IRL: Inverse Reinforcement Learning via State Marginal Matching. CoRR abs/2011.04709 (2020) - [i13]Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
C-Learning: Learning to Achieve Goals via Recursive Classification. CoRR abs/2011.08909 (2020) - [i12]Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, Sergey Levine:
ViNG: Learning Open-World Navigation with Visual Goals. CoRR abs/2012.09812 (2020) - [i11]Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Benjamin Eysenbach, Chelsea Finn, Sergey Levine:
Model-Based Visual Planning with Self-Supervised Functional Distances. CoRR abs/2012.15373 (2020)
2010 – 2019
- 2019
- [c5]Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, Sergey Levine:
Diversity is All You Need: Learning Skills without a Reward Function. ICLR (Poster) 2019 - [c4]Allan Jabri, Kyle Hsu, Abhishek Gupta, Ben Eysenbach, Sergey Levine, Chelsea Finn:
Unsupervised Curricula for Visual Meta-Reinforcement Learning. NeurIPS 2019: 10519-10530 - [c3]Ben Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
Search on the Replay Buffer: Bridging Planning and Reinforcement Learning. NeurIPS 2019: 15220-15231 - [i10]Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine:
Search on the Replay Buffer: Bridging Planning and Reinforcement Learning. CoRR abs/1906.05253 (2019) - [i9]Lisa Lee, Benjamin Eysenbach, Emilio Parisotto, Eric P. Xing, Sergey Levine, Ruslan Salakhutdinov:
Efficient Exploration via State Marginal Matching. CoRR abs/1906.05274 (2019) - [i8]Benjamin Eysenbach, Sergey Levine:
If MaxEnt RL is the Answer, What is the Question? CoRR abs/1910.01913 (2019) - [i7]Allan Jabri, Kyle Hsu, Ben Eysenbach, Abhishek Gupta, Sergey Levine, Chelsea Finn:
Unsupervised Curricula for Visual Meta-Reinforcement Learning. CoRR abs/1912.04226 (2019) - [i6]Dibya Ghosh, Abhishek Gupta, Justin Fu, Ashwin Reddy, Coline Devin, Benjamin Eysenbach, Sergey Levine:
Learning To Reach Goals Without Reinforcement Learning. CoRR abs/1912.06088 (2019) - 2018
- [j1]Bum Chul Kwon, Ben Eysenbach, Janu Verma, Kenney Ng, Christopher deFilippi, Walter F. Stewart, Adam Perer:
Clustervision: Visual Supervision of Unsupervised Clustering. IEEE Trans. Vis. Comput. Graph. 24(1): 142-151 (2018) - [c2]Benjamin Eysenbach, Shixiang Gu, Julian Ibarz, Sergey Levine:
Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning. ICLR (Poster) 2018 - [c1]John D. Co-Reyes, Yuxuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine:
Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings. ICML 2018: 1008-1017 - [i5]Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, Sergey Levine:
Diversity is All You Need: Learning Skills without a Reward Function. CoRR abs/1802.06070 (2018) - [i4]John D. Co-Reyes, Yuxuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine:
Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings. CoRR abs/1806.02813 (2018) - [i3]Abhishek Gupta, Benjamin Eysenbach, Chelsea Finn, Sergey Levine:
Unsupervised Meta-Learning for Reinforcement Learning. CoRR abs/1806.04640 (2018) - 2017
- [i2]Benjamin Eysenbach, Shixiang Gu, Julian Ibarz, Sergey Levine:
Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning. CoRR abs/1711.06782 (2017) - 2016
- [i1]Benjamin Eysenbach, Carl Vondrick, Antonio Torralba:
Who is Mistaken? CoRR abs/1612.01175 (2016)
Coauthor Index
[c38] [c35] [i49] [i47] [i44] [i43] [c33] [c32] [c31] [c30] [c28] [i42] [i41] [i39] [i38] [i37] [c27] [c26] [c25] [c24] [c22] [c21] [c20] [c18] [i35] [i34] [i33] [i32] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [i29] [i28] [i27] [i26] [i25] [i24] [i23] [i21] [i20] [c7] [i19] [i17] [i13] [i12] [i11] [c5] [c4] [c3] [i10] [i9] [i8] [i7] [i6] [c2] [c1] [i5] [i4] [i3] [i2]
Ruslan Salakhutdinov
aka: Russ Salakhutdinov
aka: Russ Salakhutdinov
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