Benjamin Eysenbach

119 papers A* 38Misc 2Journal 75Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Can We Really Learn One Representation to Optimize All Rewards? CoRR Chongyi Zheng, Royina Karegoudra Jayanth, Benjamin Eysenbach
2026	J	`jnl`	On the Role of Iterative Computation in Reinforcement Learning. CoRR Raj Ghugare, Michal Bortkiewicz, Alicja Ziarko, Benjamin Eysenbach
2026	J	`jnl`	Temporal Representations for Exploration: Learning Complex Exploratory Behavior without Extrinsic Rewards. CoRR Faisal Mohamed, Catherine Ji, Benjamin Eysenbach, Glen Berseth
2026	J	`jnl`	UpSkill: Mutual Information Skill Learning for Structured Response Diversity in LLMs. CoRR Devan Shah, Owen Yang, Daniel Yang, Chongyi Zheng, Benjamin Eysenbach
2025	J	`jnl`	1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities. CoRR Kevin Wang, Ishaan Javali, Michal Bortkiewicz, Tomasz Trzcinski, Benjamin Eysenbach
2025	A*	`conf`	A Single Goal is All You Need: Skills and Exploration Emerge from Contrastive RL without Rewards, Demonstrations, or Subgoals. ICLR Grace Liu, Michael Tang, Benjamin Eysenbach
2025	A*	`conf`	Accelerating Goal-Conditioned Reinforcement Learning Algorithms and Research. ICLR Michal Bortkiewicz, Wladyslaw Palucki, Vivek Myers, Tadeusz Dziarmaga, Tomasz Arczewski, Lukasz Kucinski, Benjamin Eysenbach
2025	J	`jnl`	BuilderBench - A benchmark for generalist agents. CoRR Raj Ghugare, Catherine Ji, Kathryn Wantlin, Jin Schofield, Benjamin Eysenbach
2025	A*	`conf`	Can a MISL Fly? Analysis and Ingredients for Mutual Information Skill Learning. ICLR Chongyi Zheng, Jens Tuyls, Joanne Peng, Benjamin Eysenbach
2025	J	`jnl`	Consistent Zero-Shot Imitation with Contrastive Goal Inference. CoRR Kathryn Wantlin, Chongyi Zheng, Benjamin Eysenbach
2025	J	`jnl`	Contrastive Representations for Temporal Reasoning. CoRR Alicja Ziarko, Michal Bortkiewicz, Michal Zawalski, Benjamin Eysenbach, Piotr Milos
2025	J	`jnl`	Demystifying the Mechanisms Behind Emergent Exploration in Goal-conditioned RL. CoRR Mahsa Bastankhah, Grace Liu, Dilip Arumugam, Thomas L. Griffiths, Benjamin Eysenbach
2025	A*	`conf`	GHIL-Glue: Hierarchical Control with Filtered Subgoal Images. ICRA Kyle Beltran Hatch, Ashwin Balakrishna, Oier Mees, Suraj Nair, Seohong Park, Blake Wulfe, Masha Itkina, Benjamin Eysenbach, Sergey Levine, Thomas Kollar, Benjamin Burchfiel
2025	A*	`conf`	Horizon Generalization in Reinforcement Learning. ICLR Vivek Myers, Catherine Ji, Benjamin Eysenbach
2025	J	`jnl`	Horizon Generalization in Reinforcement Learning. CoRR Vivek Myers, Catherine Ji, Benjamin Eysenbach
2025	J	`jnl`	Horizon Reduction Makes RL Scalable. CoRR Seohong Park, Kevin Frans, Deepinder Mann, Benjamin Eysenbach, Aviral Kumar, Sergey Levine
2025	J	`jnl`	Intention-Conditioned Flow Occupancy Models. CoRR Chongyi Zheng, Seohong Park, Sergey Levine, Benjamin Eysenbach
2025	J	`jnl`	Is Temporal Difference Learning the Gold Standard for Stitching in RL? CoRR Michal Bortkiewicz, Wladyslaw Palucki, Mateusz Ostaszewski, Benjamin Eysenbach
2025	J	`jnl`	Low-N Protein Activity Optimization with FolDE. CoRR Jacob B. Roberts, Catherine Ji, Isaac Donnell, Thomas D. Young, Allison N. Pearson, Graham A. Hudson, Leah S. Keiser, Mia Wesselkamper, Peter H. Winegar, Janik Ludwig, Sarah H. Klass, Isha V. Sheth, Ezechinyere C. Ukabiala, Maria C. T. Astolfi, Benjamin Eysenbach, Jay D. Keasling
2025	J	`jnl`	Multistep Quasimetric Learning for Scalable Goal-conditioned Reinforcement Learning. CoRR Bill Chunyuan Zheng, Vivek Myers, Benjamin Eysenbach, Sergey Levine
2025	J	`jnl`	Normalizing Flows are Capable Models for RL. CoRR Raj Ghugare, Benjamin Eysenbach
2025	A*	`conf`	OGBench: Benchmarking Offline Goal-Conditioned RL. ICLR Seohong Park, Kevin Frans, Benjamin Eysenbach, Sergey Levine
2025	J	`jnl`	Offline Goal-conditioned Reinforcement Learning with Quasimetric Representations. CoRR Vivek Myers, Bill Chunyuan Zheng, Benjamin Eysenbach, Sergey Levine
2025	J	`jnl`	SLAP: Shortcut Learning for Abstract Planning. CoRR Y. Isabel Liu, Bowen Li, Benjamin Eysenbach, Tom Silver
2025	J	`jnl`	Self-Supervised Goal-Reaching Results in Multi-Agent Cooperation and Exploration. CoRR Chirayu Nimonkar, Shlok Shah, Catherine Ji, Benjamin Eysenbach
2025	J	`jnl`	Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning. CoRR Patrik Reizinger, Bálint Mucsányi, Siyuan Guo, Benjamin Eysenbach, Bernhard Schölkopf, Wieland Brendel
2025	A*	`conf`	The "Law" of the Unconscious Contrastive Learner: Probabilistic Alignment of Unpaired Modalities. ICLR Yongwei Che, Benjamin Eysenbach
2025	J	`jnl`	The "Law" of the Unconscious Contrastive Learner: Probabilistic Alignment of Unpaired Modalities. CoRR Yongwei Che, Benjamin Eysenbach
2025	J	`jnl`	Training LLM Agents to Empower Humans. CoRR Evan Ellis, Vivek Myers, Jens Tuyls, Sergey Levine, Anca D. Dragan, Benjamin Eysenbach
2025	J	`jnl`	Value Flows. CoRR Perry Dong, Chongyi Zheng, Chelsea Finn, Dorsa Sadigh, Benjamin Eysenbach
2024	A*	`conf`	A Rate-Distortion View of Uncertainty Quantification. ICML Ifigeneia Apostolopoulou, Benjamin Eysenbach, Frank Nielsen, Artur Dubrawski
2024	J	`jnl`	A Rate-Distortion View of Uncertainty Quantification. CoRR Ifigeneia Apostolopoulou, Benjamin Eysenbach, Frank Nielsen, Artur Dubrawski
2024	J	`jnl`	A Single Goal is All You Need: Skills and Exploration Emerge from Contrastive RL without Rewards, Demonstrations, or Subgoals. CoRR Grace Liu, Michael Tang, Benjamin Eysenbach
2024	J	`jnl`	Accelerating Goal-Conditioned RL Algorithms and Research. CoRR Michal Bortkiewicz, Wladek Palucki, Vivek Myers, Tadeusz Dziarmaga, Tomasz Arczewski, Lukasz Kucinski, Benjamin Eysenbach
2024	A*	`conf`	Bridging State and History Representations: Understanding Self-Predictive RL. ICLR Tianwei Ni, Benjamin Eysenbach, Erfan Seyedsalehi, Michel Ma, Clement Gehring, Aditya Mahajan, Pierre-Luc Bacon
2024	J	`jnl`	Bridging State and History Representations: Understanding Self-Predictive RL. CoRR Tianwei Ni, Benjamin Eysenbach, Erfan Seyedsalehi, Michel Ma, Clement Gehring, Aditya Mahajan, Pierre-Luc Bacon
2024	J	`jnl`	Can a MISL Fly? Analysis and Ingredients for Mutual Information Skill Learning. CoRR Chongyi Zheng, Jens Tuyls, Joanne Peng, Benjamin Eysenbach
2024	A*	`conf`	Closing the Gap between TD Learning and Supervised Learning - A Generalisation Point of View. ICLR Raj Ghugare, Matthieu Geist, Glen Berseth, Benjamin Eysenbach
2024	J	`jnl`	Closing the Gap between TD Learning and Supervised Learning - A Generalisation Point of View. CoRR Raj Ghugare, Matthieu Geist, Glen Berseth, Benjamin Eysenbach
2024	A*	`conf`	Contrastive Difference Predictive Coding. ICLR Chongyi Zheng, Ruslan Salakhutdinov, Benjamin Eysenbach
2024	J	`jnl`	GHIL-Glue: Hierarchical Control with Filtered Subgoal Images. CoRR Kyle Beltran Hatch, Ashwin Balakrishna, Oier Mees, Suraj Nair, Seohong Park, Blake Wulfe, Masha Itkina, Benjamin Eysenbach, Sergey Levine, Thomas Kollar, Benjamin Burchfiel
2024	A*	`conf`	Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations. ICLR Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Xiangyu Liu, Benjamin Eysenbach, Tuomas Sandholm, Furong Huang, Stephen Marcus McAleer
2024	A*	`conf`	Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference. NeurIPS Benjamin Eysenbach, Vivek Myers, Ruslan Salakhutdinov, Sergey Levine
2024	J	`jnl`	Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference. CoRR Benjamin Eysenbach, Vivek Myers, Ruslan Salakhutdinov, Sergey Levine
2024	A*	`conf`	Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making. ICML Vivek Myers, Chongyi Zheng, Anca D. Dragan, Sergey Levine, Benjamin Eysenbach
2024	J	`jnl`	Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making. CoRR Vivek Myers, Chongyi Zheng, Anca D. Dragan, Sergey Levine, Benjamin Eysenbach
2024	A*	`conf`	Learning to Assist Humans without Inferring Rewards. NeurIPS Vivek Myers, Evan Ellis, Sergey Levine, Benjamin Eysenbach, Anca D. Dragan
2024	J	`jnl`	Learning to Assist Humans without Inferring Rewards. CoRR Vivek Myers, Evan Ellis, Sergey Levine, Benjamin Eysenbach, Anca D. Dragan
2024	J	`jnl`	OGBench: Benchmarking Offline Goal-Conditioned RL. CoRR Seohong Park, Kevin Frans, Benjamin Eysenbach, Sergey Levine
2024	A*	`conf`	Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data. ICLR Chongyi Zheng, Benjamin Eysenbach, Homer Rich Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine
2023	A*	`conf`	A Connection between One-Step RL and Critic Regularization in Reinforcement Learning. ICML Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov
2023	J	`jnl`	A Connection between One-Step Regularization and Critic Regularization in Reinforcement Learning. CoRR Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov
2023	A*	`conf`	Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts. ICLR Amrith Setlur, Don Kurian Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine
2023	J	`jnl`	Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts. CoRR Amrith Setlur, Don Kurian Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine
2023	J	`jnl`	Contrastive Difference Predictive Coding. CoRR Chongyi Zheng, Ruslan Salakhutdinov, Benjamin Eysenbach
2023	—	`conf`	Contrastive Example-Based Control. L4DC Kyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn
2023	J	`jnl`	Contrastive Example-Based Control. CoRR Kyle Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn
2023	Misc	`conf`	Contrastive Value Learning: Implicit Models for Simple Offline RL. CoRL Bogdan Mazoure, Benjamin Eysenbach, Ofir Nachum, Jonathan Tompson
2023	A*	`conf`	HIQL: Offline Goal-Conditioned RL with Latent States as Actions. NeurIPS Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine
2023	J	`jnl`	HIQL: Offline Goal-Conditioned RL with Latent States as Actions. CoRR Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine
2023	—	`—`	Probabilistic Reinforcement Learning: Using Data to Define Desired Outcomes and Inferring How to Get There Benjamin Eysenbach
2023	A*	`conf`	Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective. ICLR Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Russ Salakhutdinov
2023	J	`jnl`	Stabilizing Contrastive RL: Techniques for Offline Goal Reaching. CoRR Chongyi Zheng, Benjamin Eysenbach, Homer Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine
2023	A*	`conf`	When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment. NeurIPS Tianwei Ni, Michel Ma, Benjamin Eysenbach, Pierre-Luc Bacon
2023	J	`jnl`	When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment. CoRR Tianwei Ni, Michel Ma, Benjamin Eysenbach, Pierre-Luc Bacon
2022	A*	`conf`	Adversarial Unlearning: Reducing Confidence Along Adversarial Directions. NeurIPS Amrith Setlur, Benjamin Eysenbach, Virginia Smith, Sergey Levine
2022	J	`jnl`	Adversarial Unlearning: Reducing Confidence Along Adversarial Directions. CoRR Amrith Setlur, Benjamin Eysenbach, Virginia Smith, Sergey Levine
2022	A*	`conf`	C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks. ICLR Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez
2022	A*	`conf`	Contrastive Learning as Goal-Conditioned Reinforcement Learning. NeurIPS Benjamin Eysenbach, Tianjun Zhang, Sergey Levine, Ruslan Salakhutdinov
2022	J	`jnl`	Contrastive Learning as Goal-Conditioned Reinforcement Learning. CoRR Benjamin Eysenbach, Tianjun Zhang, Ruslan Salakhutdinov, Sergey Levine
2022	J	`jnl`	Contrastive Value Learning: Implicit Models for Simple Offline RL. CoRR Bogdan Mazoure, Benjamin Eysenbach, Ofir Nachum, Jonathan Tompson
2022	A*	`conf`	Imitating Past Successes can be Very Suboptimal. NeurIPS Benjamin Eysenbach, Soumith Udatha, Russ Salakhutdinov, Sergey Levine
2022	J	`jnl`	Imitating Past Successes can be Very Suboptimal. CoRR Benjamin Eysenbach, Soumith Udatha, Sergey Levine, Ruslan Salakhutdinov
2022	A*	`conf`	Learning Options via Compression. NeurIPS Yiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, J. Zico Kolter, Chelsea Finn
2022	J	`jnl`	Learning Options via Compression. CoRR Yiding Jiang, Evan Zheran Liu, Benjamin Eysenbach, Zico Kolter, Chelsea Finn
2022	A*	`conf`	Maximum Entropy RL (Provably) Solves Some Robust RL Problems. ICLR Benjamin Eysenbach, Sergey Levine
2022	A*	`conf`	Mismatched No More: Joint Model-Policy Optimization for Model-Based RL. NeurIPS Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov
2022	A*	`conf`	Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs. ICML Tianwei Ni, Benjamin Eysenbach, Ruslan Salakhutdinov
2022	A*	`conf`	RvS: What is Essential for Offline RL via Supervised Learning? ICLR Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine
2022	J	`jnl`	Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective. CoRR Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Ruslan Salakhutdinov
2022	A*	`conf`	The Information Geometry of Unsupervised Reinforcement Learning. ICLR Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
2021	A*	`conf`	Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills. ICML Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jacob Varley, Alex Irpan, Benjamin Eysenbach, Ryan Julian, Chelsea Finn, Sergey Levine
2021	J	`jnl`	Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills. CoRR Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jake Varley, Alex Irpan, Benjamin Eysenbach, Ryan Julian, Chelsea Finn, Sergey Levine
2021	A*	`conf`	C-Learning: Learning to Achieve Goals via Recursive Classification. ICLR Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
2021	J	`jnl`	C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks. CoRR Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez
2021	A*	`conf`	Learning to Reach Goals via Iterated Supervised Learning. ICLR Dibya Ghosh, Abhishek Gupta, Ashwin Reddy, Justin Fu, Coline Manon Devin, Benjamin Eysenbach, Sergey Levine
2021	J	`jnl`	Maximum Entropy RL (Provably) Solves Some Robust RL Problems. CoRR Benjamin Eysenbach, Sergey Levine
2021	J	`jnl`	Mismatched No More: Joint Model-Policy Optimization for Model-Based RL. CoRR Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov
2021	A*	`conf`	Model-Based Visual Planning with Self-Supervised Functional Distances. ICLR Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Benjamin Eysenbach, Chelsea Finn, Sergey Levine
2021	A*	`conf`	Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers. ICLR Benjamin Eysenbach, Shreyas Chaudhari, Swapnil Asawa, Sergey Levine, Ruslan Salakhutdinov
2021	J	`jnl`	RECON: Rapid Exploration for Open-World Navigation with Latent Goal Models. CoRR Dhruv Shah, Benjamin Eysenbach, Nicholas Rhinehart, Sergey Levine
2021	Misc	`conf`	Rapid Exploration for Open-World Navigation with Latent Goal Models. CoRL Dhruv Shah, Benjamin Eysenbach, Nicholas Rhinehart, Sergey Levine
2021	J	`jnl`	Recurrent Model-Free RL is a Strong Baseline for Many POMDPs. CoRR Tianwei Ni, Benjamin Eysenbach, Ruslan Salakhutdinov
2021	J	`jnl`	Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification. CoRR Benjamin Eysenbach, Sergey Levine, Ruslan Salakhutdinov
2021	J	`jnl`	Robust Predictable Control. CoRR Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
2021	J	`jnl`	RvS: What is Essential for Offline RL via Supervised Learning? CoRR Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine
2021	J	`jnl`	The Information Geometry of Unsupervised Reinforcement Learning. CoRR Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
2021	A*	`conf`	ViNG: Learning Open-World Navigation with Visual Goals. ICRA Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, Sergey Levine
2020	J	`jnl`	C-Learning: Learning to Achieve Goals via Recursive Classification. CoRR Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
2020	J	`jnl`	Interactive Visualization for Debugging RL. CoRR Shuby Deshpande, Benjamin Eysenbach, Jeff Schneider
2020	J	`jnl`	Learning to be Safe: Deep RL with a Safety Critic. CoRR Krishnan Srinivasan, Benjamin Eysenbach, Sehoon Ha, Jie Tan, Chelsea Finn
2020	J	`jnl`	Model-Based Visual Planning with Self-Supervised Functional Distances. CoRR Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Benjamin Eysenbach, Chelsea Finn, Sergey Levine
2020	J	`jnl`	Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers. CoRR Benjamin Eysenbach, Swapnil Asawa, Shreyas Chaudhari, Ruslan Salakhutdinov, Sergey Levine
2020	J	`jnl`	Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement. CoRR Benjamin Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov
2020	J	`jnl`	ViNG: Learning Open-World Navigation with Visual Goals. CoRR Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, Sergey Levine
2020	J	`jnl`	Weakly-Supervised Reinforcement Learning for Controllable Behavior. CoRR Lisa Lee, Benjamin Eysenbach, Ruslan Salakhutdinov, Shixiang Gu, Chelsea Finn
2020	J	`jnl`	f-IRL: Inverse Reinforcement Learning via State Marginal Matching. CoRR Tianwei Ni, Harshit S. Sikchi, Yufei Wang, Tejus Gupta, Lisa Lee, Benjamin Eysenbach
2019	—	`conf`	Diversity is All You Need: Learning Skills without a Reward Function. ICLR (Poster) Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, Sergey Levine
2019	J	`jnl`	Efficient Exploration via State Marginal Matching. CoRR Lisa Lee, Benjamin Eysenbach, Emilio Parisotto, Eric P. Xing, Sergey Levine, Ruslan Salakhutdinov
2019	J	`jnl`	If MaxEnt RL is the Answer, What is the Question? CoRR Benjamin Eysenbach, Sergey Levine
2019	J	`jnl`	Learning To Reach Goals Without Reinforcement Learning. CoRR Dibya Ghosh, Abhishek Gupta, Justin Fu, Ashwin Reddy, Coline Devin, Benjamin Eysenbach, Sergey Levine
2019	J	`jnl`	Search on the Replay Buffer: Bridging Planning and Reinforcement Learning. CoRR Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
2018	J	`jnl`	Diversity is All You Need: Learning Skills without a Reward Function. CoRR Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, Sergey Levine
2018	—	`conf`	Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning. ICLR (Poster) Benjamin Eysenbach, Shixiang Gu, Julian Ibarz, Sergey Levine
2018	A*	`conf`	Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings. ICML John D. Co-Reyes, Yuxuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings. CoRR John D. Co-Reyes, Yuxuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	Unsupervised Meta-Learning for Reinforcement Learning. CoRR Abhishek Gupta, Benjamin Eysenbach, Chelsea Finn, Sergey Levine
2017	J	`jnl`	Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning. CoRR Benjamin Eysenbach, Shixiang Gu, Julian Ibarz, Sergey Levine
2016	J	`jnl`	Who is Mistaken? CoRR Benjamin Eysenbach, Carl Vondrick, Antonio Torralba