Eysenbach, Benjamin

75 publications

NeurIPS 2025 1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities Kevin Wang, Ishaan Javali, Michał Bortkiewicz, Tomasz Trzcinski, Benjamin Eysenbach

ICLR 2025 A Single Goal Is All You Need: Skills and Exploration Emerge from Contrastive RL Without Rewards, Demonstrations, or Subgoals Grace Liu, Michael Tang, Benjamin Eysenbach

ICLRW 2025 Accelerating Goal-Conditioned RL Algorithms and Research Michał Bortkiewicz, Władysław Pałucki, Vivek Myers, Tadeusz Dziarmaga, Tomasz Arczewski, Łukasz Kuciński, Benjamin Eysenbach

ICLR 2025 Accelerating Goal-Conditioned Reinforcement Learning Algorithms and Research Michał Bortkiewicz, Władysław Pałucki, Vivek Myers, Tadeusz Dziarmaga, Tomasz Arczewski, Łukasz Kuciński, Benjamin Eysenbach

ICLR 2025 Can a MISL Fly? Analysis and Ingredients for Mutual Information Skill Learning Chongyi Zheng, Jens Tuyls, Joanne Peng, Benjamin Eysenbach

ICLRW 2025 Contrastive Representations for Combinatorial Reasoning Alicja Ziarko, Michał Bortkiewicz, Michał Zawalski, Benjamin Eysenbach, Piotr Miłoś

NeurIPS 2025 Contrastive Representations for Temporal Reasoning Alicja Ziarko, Michał Bortkiewicz, Michał Zawalski, Benjamin Eysenbach, Piotr Miłoś

ICLR 2025 Horizon Generalization in Reinforcement Learning Vivek Myers, Catherine Ji, Benjamin Eysenbach

NeurIPS 2025 Horizon Reduction Makes RL Scalable Seohong Park, Kevin Frans, Deepinder Mann, Benjamin Eysenbach, Aviral Kumar, Sergey Levine

NeurIPS 2025 Normalizing Flows Are Capable Models for Continuous Control Raj Ghugare, Benjamin Eysenbach

ICLR 2025 OGBench: Benchmarking Offline Goal-Conditioned RL Seohong Park, Kevin Frans, Benjamin Eysenbach, Sergey Levine

NeurIPS 2025 Offline Goal-Conditioned Reinforcement Learning with Quasimetric Representations Vivek Myers, Bill Zheng, Benjamin Eysenbach, Sergey Levine

ICLR 2025 The "Law'' of the Unconscious Contrastive Learner: Probabilistic Alignment of Unpaired Modalities Yongwei Che, Benjamin Eysenbach

ICML 2024 A Rate-Distortion View of Uncertainty Quantification Ifigeneia Apostolopoulou, Benjamin Eysenbach, Frank Nielsen, Artur Dubrawski

NeurIPSW 2024 A Single Goal Is All You Need Grace Liu, Michael Tang, Benjamin Eysenbach

ICLR 2024 Bridging State and History Representations: Understanding Self-Predictive RL Tianwei Ni, Benjamin Eysenbach, Erfan SeyedSalehi, Michel Ma, Clement Gehring, Aditya Mahajan, Pierre-Luc Bacon

NeurIPSW 2024 Can a MISL Fly? Analysis and Ingredients for Mutual Information Skill Learning Chongyi Zheng, Jens Tuyls, Joanne Peng, Benjamin Eysenbach

ICLR 2024 Closing the Gap Between TD Learning and Supervised Learning - A Generalisation Point of View. Raj Ghugare, Matthieu Geist, Glen Berseth, Benjamin Eysenbach

ICLR 2024 Contrastive Difference Predictive Coding Chongyi Zheng, Ruslan Salakhutdinov, Benjamin Eysenbach

ICLR 2024 Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations Yongyuan Liang, Yanchao Sun, Ruijie Zheng, Xiangyu Liu, Benjamin Eysenbach, Tuomas Sandholm, Furong Huang, Stephen Marcus McAleer

NeurIPS 2024 Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference Benjamin Eysenbach, Vivek Myers, Ruslan Salakhutdinov, Sergey Levine

ICML 2024 Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making Vivek Myers, Chongyi Zheng, Anca Dragan, Sergey Levine, Benjamin Eysenbach

NeurIPS 2024 Learning to Assist Humans Without Inferring Rewards Vivek Myers, Evan Ellis, Sergey Levine, Benjamin Eysenbach, Anca Dragan

ICMLW 2024 Learning to Assist Humans Without Inferring Rewards Vivek Myers, Evan Ellis, Benjamin Eysenbach, Sergey Levine, Anca Dragan

ICLR 2024 Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data Chongyi Zheng, Benjamin Eysenbach, Homer Rich Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine

ICML 2023 A Connection Between One-Step RL and Critic Regularization in Reinforcement Learning Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov

ICLR 2023 Bitrate-Constrained DRO: Beyond Worst Case Robustness to Unknown Group Shifts Amrith Setlur, Don Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine

NeurIPSW 2023 Closing the Gap Between TD Learning and Supervised Learning -- a Generalisation Point of View. Raj Ghugare, Matthieu Geist, Glen Berseth, Benjamin Eysenbach

NeurIPSW 2023 Closing the Gap Between TD Learning and Supervised Learning -- a Generalisation Point of View. Raj Ghugare, Matthieu Geist, Glen Berseth, Benjamin Eysenbach

NeurIPSW 2023 Contrastive Difference Predictive Coding Chongyi Zheng, Ruslan Salakhutdinov, Benjamin Eysenbach

L4DC 2023 Contrastive Example-Based Control Kyle Beltran Hatch, Benjamin Eysenbach, Rafael Rafailov, Tianhe Yu, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn

NeurIPSW 2023 Contrastive Representations Make Planning Easy Benjamin Eysenbach, Vivek Myers, Sergey Levine, Ruslan Salakhutdinov

CoRL 2023 Contrastive Value Learning: Implicit Models for Simple Offline RL Bogdan Mazoure, Benjamin Eysenbach, Ofir Nachum, Jonathan Tompson

ICMLW 2023 Distributional Distance Classifiers for Goal-Conditioned Reinforcement Learning Ravi Tej Akella, Benjamin Eysenbach, Jeff Schneider, Ruslan Salakhutdinov

NeurIPS 2023 HIQL: Offline Goal-Conditioned RL with Latent States as Actions Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine

ICMLW 2023 Offline Goal-Conditioned RL with Latent States as Actions Seohong Park, Dibya Ghosh, Benjamin Eysenbach, Sergey Levine

ICLR 2023 Simplifying Model-Based RL: Learning Representations, Latent-Space Models, and Policies with One Objective Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Russ Salakhutdinov

NeurIPSW 2023 Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data Chongyi Zheng, Benjamin Eysenbach, Homer Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine

NeurIPSW 2023 Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data Chongyi Zheng, Benjamin Eysenbach, Homer Walke, Patrick Yin, Kuan Fang, Ruslan Salakhutdinov, Sergey Levine

NeurIPS 2023 When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment Tianwei Ni, Michel Ma, Benjamin Eysenbach, Pierre-Luc Bacon

NeurIPSW 2023 When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment Tianwei Ni, Michel Ma, Benjamin Eysenbach, Pierre-Luc Bacon

NeurIPSW 2022 A Connection Between One-Step Regularization and Critic Regularization in Reinforcement Learning Benjamin Eysenbach, Matthieu Geist, Ruslan Salakhutdinov, Sergey Levine

NeurIPSW 2022 A Connection Between One-Step Regularization and Critic Regularization in Reinforcement Learning Benjamin Eysenbach, Matthieu Geist, Sergey Levine, Ruslan Salakhutdinov

NeurIPS 2022 Adversarial Unlearning: Reducing Confidence Along Adversarial Directions Amrith Setlur, Benjamin Eysenbach, Virginia Smith, Sergey Levine

ICLRW 2022 An Empirical Investigation of Mutual Information Skill Learning Faisal Mohamed, Benjamin Eysenbach, Russ Salakhutdinov

NeurIPSW 2022 Bitrate-Constrained DRO: Beyond Worst Case Robustness to Unknown Group Shifts Amrith Setlur, Don Dennis, Benjamin Eysenbach, Aditi Raghunathan, Chelsea Finn, Virginia Smith, Sergey Levine

ICLR 2022 C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez

NeurIPSW 2022 Contrastive Example-Based Control Kyle Beltran Hatch, Sarthak J Shetty, Benjamin Eysenbach, Tianhe Yu, Rafael Rafailov, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn

NeurIPSW 2022 Contrastive Example-Based Control Kyle Beltran Hatch, Sarthak J Shetty, Benjamin Eysenbach, Tianhe Yu, Rafael Rafailov, Ruslan Salakhutdinov, Sergey Levine, Chelsea Finn

NeurIPS 2022 Contrastive Learning as Goal-Conditioned Reinforcement Learning Benjamin Eysenbach, Tianjun Zhang, Sergey Levine, Ruslan Salakhutdinov

NeurIPSW 2022 Contrastive Value Learning: Implicit Models for Simple Offline RL Bogdan Mazoure, Benjamin Eysenbach, Ofir Nachum, Jonathan Tompson

NeurIPS 2022 Imitating past Successes Can Be Very Suboptimal Benjamin Eysenbach, Soumith Udatha, Ruslan Salakhutdinov, Sergey Levine

NeurIPS 2022 Learning Options via Compression Yiding Jiang, Evan Liu, Benjamin Eysenbach, J. Zico Kolter, Chelsea Finn

ICLRW 2022 Maximizing Entropy on Adversarial Examples Can Improve Generalization Amrith Setlur, Benjamin Eysenbach, Virginia Smith, Sergey Levine

ICLR 2022 Maximum Entropy RL (Provably) Solves Some Robust RL Problems Benjamin Eysenbach, Sergey Levine

NeurIPS 2022 Mismatched No More: Joint Model-Policy Optimization for Model-Based RL Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov

ICML 2022 Recurrent Model-Free RL Can Be a Strong Baseline for Many POMDPs Tianwei Ni, Benjamin Eysenbach, Ruslan Salakhutdinov

ICLR 2022 RvS: What Is Essential for Offline RL via Supervised Learning? Scott Emmons, Benjamin Eysenbach, Ilya Kostrikov, Sergey Levine

NeurIPSW 2022 Simplifying Model-Based RL: Learning Representations, Latent-Space Models, and Policies with One Objective Raj Ghugare, Homanga Bharadhwaj, Benjamin Eysenbach, Sergey Levine, Russ Salakhutdinov

ICLR 2022 The Information Geometry of Unsupervised Reinforcement Learning Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine

ICML 2021 Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills Yevgen Chebotar, Karol Hausman, Yao Lu, Ted Xiao, Dmitry Kalashnikov, Jacob Varley, Alex Irpan, Benjamin Eysenbach, Ryan C Julian, Chelsea Finn, Sergey Levine

ICLR 2021 C-Learning: Learning to Achieve Goals via Recursive Classification Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine

NeurIPSW 2021 C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks Tianjun Zhang, Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine, Joseph E. Gonzalez

ICLR 2021 Learning to Reach Goals via Iterated Supervised Learning Dibya Ghosh, Abhishek Gupta, Ashwin Reddy, Justin Fu, Coline Manon Devin, Benjamin Eysenbach, Sergey Levine

NeurIPSW 2021 Mismatched No More: Joint Model-Policy Optimization for Model-Based RL Benjamin Eysenbach, Alexander Khazatsky, Sergey Levine, Ruslan Salakhutdinov

ICLR 2021 Model-Based Visual Planning with Self-Supervised Functional Distances Stephen Tian, Suraj Nair, Frederik Ebert, Sudeep Dasari, Benjamin Eysenbach, Chelsea Finn, Sergey Levine

ICLR 2021 Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers Benjamin Eysenbach, Shreyas Chaudhari, Swapnil Asawa, Sergey Levine, Ruslan Salakhutdinov

CoRL 2021 Rapid Exploration for Open-World Navigation with Latent Goal Models Dhruv Shah, Benjamin Eysenbach, Nicholas Rhinehart, Sergey Levine

NeurIPSW 2021 The Information Geometry of Unsupervised Reinforcement Learning Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine

ICMLW 2020 Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers Benjamin Eysenbach, Swapnil Asawa, Shreyas Chaudhari, Ruslan Salakhutdinov, Sergey Levine

ICMLW 2020 Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement Benjamin Eysenbach, Xinyang Geng, Sergey Levine, Ruslan Salakhutdinov

ICLR 2020 Unsupervised Meta-Learning for Reinforcement Learning Abhishek Gupta, Benjamin Eysenbach, Chelsea Finn, Sergey Levine

ICLR 2019 Diversity Is All You Need: Learning Skills Without a Reward Function Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz, Sergey Levine

ICLR 2018 Leave No Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning Benjamin Eysenbach, Shixiang Gu, Julian Ibarz, Sergey Levine

ICML 2018 Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings John Co-Reyes, YuXuan Liu, Abhishek Gupta, Benjamin Eysenbach, Pieter Abbeel, Sergey Levine