Oh, Junhyuk

26 publications

NeurIPS 2025 DataRater: Meta-Learned Dataset Curation Dan A. Calian, Gregory Farquhar, Iurii Kemaev, Luisa Zintgraf, Matteo Hessel, Jeremy Shar, Junhyuk Oh, András György, Tom Schaul, Jeff Dean, Hado van Hasselt, David Silver

ICLR 2025 Learning from Negative Feedback, or Positive Feedback or Both Abbas Abdolmaleki, Bilal Piot, Bobak Shahriari, Jost Tobias Springenberg, Tim Hertweck, Michael Bloesch, Rishabh Joshi, Thomas Lampe, Junhyuk Oh, Nicolas Heess, Jonas Buchli, Martin Riedmiller

NeurIPS 2023 Deep Reinforcement Learning with Plasticity Injection Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, Andre Barreto

ICLRW 2023 Deep Reinforcement Learning with Plasticity Injection Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, Andre Barreto

ICLR 2023 In-Context Reinforcement Learning with Algorithm Distillation Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, Dj Strouse, Steven Stenberg Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih

NeurIPSW 2022 In-Context Reinforcement Learning with Algorithm Distillation Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, Dj Strouse, Steven Stenberg Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih

NeurIPSW 2022 In-Context Reinforcement Learning with Algorithm Distillation Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, Dj Strouse, Steven Stenberg Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih

AAAI 2022 Introducing Symmetries to Black Box Meta Reinforcement Learning Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen

ICLR 2021 Balancing Constraints and Rewards with Meta-Gradient D4PG Dan A. Calian, Daniel J Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy Mann

NeurIPS 2021 Discovery of Options via Meta-Learned Subgoals Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado P van Hasselt, David Silver, Satinder P. Singh

NeurIPSW 2021 Introducing Symmetries to Black Box Meta Reinforcement Learning Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen

NeurIPSW 2021 Introducing Symmetries to Black Box Meta Reinforcement Learning Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen

NeurIPS 2020 A Self-Tuning Actor-Critic Algorithm Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado P van Hasselt, David Silver, Satinder P. Singh

NeurIPS 2020 Discovering Reinforcement Learning Algorithms Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado P van Hasselt, Satinder P. Singh, David Silver

NeurIPS 2020 Meta-Gradient Reinforcement Learning with an Objective Discovered Online Zhongwen Xu, Hado P van Hasselt, Matteo Hessel, Junhyuk Oh, Satinder P. Singh, David Silver

ICML 2020 What Can Learned Intrinsic Rewards Capture? Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado Van Hasselt, David Silver, Satinder Singh

ICLR 2019 Contingency-Aware Exploration in Reinforcement Learning Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu, Mohammad Norouzi, Honglak Lee

NeurIPS 2019 Discovery of Useful Questions as Auxiliary Tasks Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Janarthanan Rajendran, Richard L. Lewis, Junhyuk Oh, Hado P van Hasselt, David Silver, Satinder Singh

NeurIPS 2018 Hierarchical Reinforcement Learning for Zero-Shot Generalization with Subtask Dependencies Sungryull Sohn, Junhyuk Oh, Honglak Lee

NeurIPS 2018 On Learning Intrinsic Rewards for Policy Gradient Methods Zeyu Zheng, Junhyuk Oh, Satinder Singh

ICML 2018 Self-Imitation Learning Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee

NeurIPS 2017 Value Prediction Network Junhyuk Oh, Satinder Singh, Honglak Lee

ICML 2017 Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli

ICML 2016 Control of Memory, Active Perception, and Action in Minecraft Junhyuk Oh, Valliappa Chockalingam, Satinder, Honglak Lee

CVPR 2016 Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network Seunghoon Hong, Junhyuk Oh, Honglak Lee, Bohyung Han

NeurIPS 2015 Action-Conditional Video Prediction Using Deep Networks in Atari Games Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L. Lewis, Satinder Singh