Berseth, Glen

45 publications

TMLR 2025 Adaptive Resolution Residual Networks — Generalizing Across Resolutions Easily and Efficiently Léa Demeule, Mahtab Sandhu, Glen Berseth

ICLR 2025 Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference Matthew Riemer, Gopeshh Subbaraj, Glen Berseth, Irina Rish

ICML 2025 Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn Hongyao Tang, Johan Obando-Ceron, Pablo Samuel Castro, Aaron Courville, Glen Berseth

ICLR 2025 Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching Arnav Kumar Jain, Harley Wiltzer, Jesse Farebrother, Irina Rish, Glen Berseth, Sanjiban Choudhury

ICML 2025 Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models Siddarth Venkatraman, Mohsin Hasan, Minsu Kim, Luca Scimeca, Marcin Sendera, Yoshua Bengio, Glen Berseth, Nikolay Malkin

ICLRW 2025 Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models Siddarth Venkatraman, Mohsin Hasan, Minsu Kim, Luca Scimeca, Marcin Sendera, Yoshua Bengio, Glen Berseth, Nikolay Malkin

TMLR 2025 RLeXplore: Accelerating Research in Intrinsically-Motivated Reinforcement Learning Mingqi Yuan, Roger Creus Castanyer, Bo Li, Xin Jin, Wenjun Zeng, Glen Berseth

CoRL 2025 RoboArena: Distributed Real-World Evaluation of Generalist Robot Policies Pranav Atreya, Karl Pertsch, Tony Lee, Moo Jin Kim, Arhan Jain, Artur Kuramshin, Cyrus Neary, Edward S. Hu, Kanav Arora, Kirsty Ellis, Luca Macesanu, Matthew Leonard, Meedeum Cho, Ozgur Aslan, Shivin Dass, Tony Wang, Xingfang Yuan, Abhishek Gupta, Dinesh Jayaraman, Glen Berseth, Kostas Daniilidis, Roberto Martín-Martín, Youngwoon Lee, Percy Liang, Chelsea Finn, Sergey Levine

ICLRW 2025 Solving Bayesian Inverse Problems with Diffusion Priors and Off-Policy RL Luca Scimeca, Siddarth Venkatraman, Moksh Jain, Minsu Kim, Marcin Sendera, Mohsin Hasan, Alexandre Adam, Yashar Hezaveh, Laurence Perreault-Levasseur, Yoshua Bengio, Glen Berseth, Nikolay Malkin

NeurIPS 2025 Stable Gradients for Stable Learning at Scale in Deep Reinforcement Learning Roger Creus Castanyer, Johan Obando-Ceron, Lu Li, Pierre-Luc Bacon, Glen Berseth, Aaron Courville, Pablo Samuel Castro

ICLR 2025 Towards Improving Exploration Through Sibling Augmented GFlowNets Kanika Madan, Alex Lamb, Emmanuel Bengio, Glen Berseth, Yoshua Bengio

NeurIPS 2024 Amortizing Intractable Inference in Diffusion Models for Vision, Language, and Control Siddarth Venkatraman, Moksh Jain, Luca Scimeca, Minsu Kim, Marcin Sendera, Mohsin Hasan, Luke Rowe, Sarthak Mittal, Pablo Lemos, Emmanuel Bengio, Alexandre Adam, Jarrid Rector-Brooks, Yoshua Bengio, Glen Berseth, Nikolay Malkin

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

NeurIPSW 2024 Efficient Design-and-Control Automation with Reinforcement Learning and Adaptive Exploration Jiajun Fan, Hongyao Tang, Michael Przystupa, Mariano Phielipp, Santiago Miret, Glen Berseth

NeurIPS 2024 Improving Deep Reinforcement Learning by Reducing the Chain Effect of Value and Policy Churn Hongyao Tang, Glen Berseth

ICLR 2024 Improving Intrinsic Exploration by Creating Stationary Objectives Roger Creus Castanyer, Joshua Romoff, Glen Berseth

ICLR 2024 Intelligent Switching for Reset-Free RL Darshan Patil, Janarthanan Rajendran, Glen Berseth, Sarath Chandar

ICMLW 2024 Realtime Reinforcement Learning: Towards Rapid Asynchronous Deployment of Large Models Matthew Riemer, Gopeshh Subbaraj, Glen Berseth, Irina Rish

ICLR 2024 Reasoning with Latent Diffusion in Offline Reinforcement Learning Siddarth Venkatraman, Shivesh Khaitan, Ravi Tej Akella, John Dolan, Jeff Schneider, Glen Berseth

ICMLW 2024 Revisiting Successor Features for Inverse Reinforcement Learning Arnav Kumar Jain, Harley Wiltzer, Jesse Farebrother, Irina Rish, Glen Berseth, Sanjiban Choudhury

ICLR 2024 Searching for High-Value Molecules Using Reinforcement Learning and Transformers Raj Ghugare, Santiago Miret, Adriana Hugessen, Mariano Phielipp, Glen Berseth

NeurIPS 2024 Simplifying Constraint Inference with Inverse Reinforcement Learning Adriana Hugessen, Harley Wiltzer, Glen Berseth

NeurIPSW 2023 Adaptive Resolution Residual Networks Léa Demeule, Mahtab Sandhu, Glen Berseth

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 Improving Intrinsic Exploration by Creating Stationary Objectives Roger Creus Castanyer, Joshua Romoff, Glen Berseth

NeurIPS 2023 Maximum State Entropy Exploration Using Predecessor and Successor Representations Arnav Kumar Jain, Lucas Lehnert, Irina Rish, Glen Berseth

ICMLW 2023 Maximum State Entropy Exploration Using Predecessor and Successor Representations Arnav Kumar Jain, Lucas Lehnert, Irina Rish, Glen Berseth

NeurIPSW 2023 Searching for High-Value Molecules Using Reinforcement Learning and Transformers Raj Ghugare, Santiago Miret, Adriana Hugessen, Mariano Phielipp, Glen Berseth

NeurIPSW 2023 Surprise-Adaptive Intrinsic Motivation for Unsupervised Reinforcement Learning Adriana Hugessen, Roger Creus Castanyer, Glen Berseth

JMLR 2023 Towards Learning to Imitate from a Single Video Demonstration Glen Berseth, Florian Golemo, Christopher Pal

ICML 2022 AnyMorph: Learning Transferable Polices by Inferring Agent Morphology Brandon Trabucco, Mariano Phielipp, Glen Berseth

ICLR 2022 CoMPS: Continual Meta Policy Search Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn, Sergey Levine

ICLRW 2022 Generalization Games for Reinforcement Learning Manfred Diaz, Charlie Gauthier, Glen Berseth, Liam Paull

ICLRW 2022 Learning Transferable Policies by Inferring Agent Morphology Brandon Trabucco, Mariano Phielipp, Glen Berseth

ICLRW 2021 Accelerating Online Reinforcement Learning via Model-Based Meta-Learning John D Co-Reyes, Sarah Feng, Glen Berseth, Jie Qui, Sergey Levine

NeurIPSW 2021 CoMPS: Continual Meta Policy Search Glen Berseth, Zhiwei Zhang, Grace Zhang, Chelsea Finn, Sergey Levine

ICMLW 2021 Explore and Control with Adversarial Surprise Arnaud Fickinger, Natasha Jaques, Samyak Parajuli, Michael Chang, Nicholas Rhinehart, Glen Berseth, Stuart Russell, Sergey Levine

CoRL 2021 Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation Charles Sun, Jȩdrzej Orbik, Coline Manon Devin, Brian H. Yang, Abhishek Gupta, Glen Berseth, Sergey Levine

NeurIPS 2021 Information Is Power: Intrinsic Control via Information Capture Nicholas Rhinehart, Jenny Wang, Glen Berseth, John Co-Reyes, Danijar Hafner, Chelsea Finn, Sergey Levine

ICMLW 2021 Intrinsic Control of Variational Beliefs in Dynamic Partially-Observed Visual Environments Nicholas Rhinehart, Jenny Wang, Glen Berseth, John D Co-Reyes, Danijar Hafner, Chelsea Finn, Sergey Levine

ICLR 2021 SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments Glen Berseth, Daniel Geng, Coline Manon Devin, Nicholas Rhinehart, Chelsea Finn, Dinesh Jayaraman, Sergey Levine

ICLR 2021 X2T: Training an X-to-Text Typing Interface with Online Learning from User Feedback Jensen Gao, Siddharth Reddy, Glen Berseth, Nicholas Hardy, Nikhilesh Natraj, Karunesh Ganguly, Anca Dragan, Sergey Levine

CoRL 2019 Contextual Imagined Goals for Self-Supervised Robotic Learning Ashvin Nair, Shikhar Bahl, Alexander Khazatsky, Vitchyr Pong, Glen Berseth, Sergey Levine

ICLR 2018 Progressive Reinforcement Learning with Distillation for Multi-Skilled Motion Control Glen Berseth, Cheng Xie, Paul Cernek, Michiel Van de Panne