Junhyuk Oh - RankMe

49 papers A* 17A 1Journal 27Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	DataRater: Meta-Learned Dataset Curation. CoRR Dan A. Calian, Gregory Farquhar, Iurii Kemaev, Luisa M. Zintgraf, Matteo Hessel, Jeremy Shar, Junhyuk Oh, András György, Tom Schaul, Jeffrey Dean, Hado van Hasselt, David Silver
2025	J	`jnl`	Discovering state-of-the-art reinforcement learning algorithms. Nat. Junhyuk Oh, Gregory Farquhar, Iurii Kemaev, Dan A. Calian, Matteo Hessel, Luisa M. Zintgraf, Satinder Singh, Hado van Hasselt, David Silver
2025	A*	`conf`	Learning from negative feedback, or positive feedback or both. ICLR Abbas Abdolmaleki, Bilal Piot, Bobak Shahriari, Jost Tobias Springenberg, Tim Hertweck, Michael Bloesch, Rishabh Joshi, Thomas Lampe, Junhyuk Oh, Nicolas Heess, Jonas Buchli, Martin A. Riedmiller
2024	J	`jnl`	Preference Optimization as Probabilistic Inference. CoRR Abbas Abdolmaleki, Bilal Piot, Bobak Shahriari, Jost Tobias Springenberg, Tim Hertweck, Rishabh Joshi, Junhyuk Oh, Michael Bloesch, Thomas Lampe, Nicolas Heess, Jonas Buchli, Martin A. Riedmiller
2023	A*	`conf`	Deep Reinforcement Learning with Plasticity Injection. NeurIPS Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, André Barreto
2023	J	`jnl`	Deep Reinforcement Learning with Plasticity Injection. CoRR Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, André Barreto
2023	A*	`conf`	In-context Reinforcement Learning with Algorithm Distillation. ICLR 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
2022	J	`jnl`	In-context Reinforcement Learning with Algorithm Distillation. CoRR Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih
2022	A*	`conf`	Introducing Symmetries to Black Box Meta Reinforcement Learning. AAAI Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen
2021	A*	`conf`	Balancing Constraints and Rewards with Meta-Gradient D4PG. ICLR Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A. Mann
2021	A*	`conf`	Discovery of Options via Meta-Learned Subgoals. NeurIPS Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh
2021	J	`jnl`	Discovery of Options via Meta-Learned Subgoals. CoRR Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh
2021	J	`jnl`	Introducing Symmetries to Black Box Meta Reinforcement Learning. CoRR Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen
2021	A	`conf`	Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity. AAMAS Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu, Dhruva Tirumala, Junhyuk Oh, Gauthier Gidel, Hado van Hasselt, David Balduzzi
2021	J	`jnl`	Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity. CoRR Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu, Dhruva Tirumala, Junhyuk Oh, Gauthier Gidel, Hado van Hasselt, David Balduzzi
2020	A*	`conf`	A Self-Tuning Actor-Critic Algorithm. NeurIPS Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
2020	J	`jnl`	Balancing Constraints and Rewards with Meta-Gradient D4PG. CoRR Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A. Mann
2020	A*	`conf`	Discovering Reinforcement Learning Algorithms. NeurIPS Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado van Hasselt, Satinder Singh, David Silver
2020	J	`jnl`	Discovering Reinforcement Learning Algorithms. CoRR Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado van Hasselt, Satinder Singh, David Silver
2020	A*	`conf`	Meta-Gradient Reinforcement Learning with an Objective Discovered Online. NeurIPS Zhongwen Xu, Hado Philip van Hasselt, Matteo Hessel, Junhyuk Oh, Satinder Singh, David Silver
2020	J	`jnl`	Meta-Gradient Reinforcement Learning with an Objective Discovered Online. CoRR Zhongwen Xu, Hado van Hasselt, Matteo Hessel, Junhyuk Oh, Satinder Singh, David Silver
2020	J	`jnl`	Self-Tuning Deep Reinforcement Learning. CoRR Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
2020	A*	`conf`	What Can Learned Intrinsic Rewards Capture? ICML Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh
2019	—	`conf`	Contingency-Aware Exploration in Reinforcement Learning. ICLR (Poster) Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu, Mohammad Norouzi, Honglak Lee
2019	A*	`conf`	Discovery of Useful Questions as Auxiliary Tasks. NeurIPS Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Janarthanan Rajendran, Richard L. Lewis, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
2019	J	`jnl`	Discovery of Useful Questions as Auxiliary Tasks. CoRR Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Richard L. Lewis, Janarthanan Rajendran, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
2019	J	`jnl`	Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nat. Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds, Petko Georgiev, Junhyuk Oh, Dan Horgan, Manuel Kroiss, Ivo Danihelka, Aja Huang, Laurent Sifre, Trevor Cai, John P. Agapiou, Max Jaderberg, Alexander Sasha Vezhnevets, Rémi Leblond, Tobias Pohlen, Valentin Dalibard, David Budden, Yury Sulsky, James Molloy, Tom Le Paine, Çaglar Gülçehre, Ziyu Wang, Tobias Pfaff, Yuhuai Wu, Roman Ring, Dani Yogatama, Dario Wünsch, Katrina McKinney, Oliver Smith, Tom Schaul, Timothy P. Lillicrap, Koray Kavukcuoglu, Demis Hassabis, Chris Apps, David Silver
2019	J	`jnl`	What Can Learned Intrinsic Rewards Capture? CoRR Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh
2018	J	`jnl`	Contingency-Aware Exploration in Reinforcement Learning. CoRR Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu, Mohammad Norouzi, Honglak Lee
2018	—	`—`	Efficient Deep Reinforcement Learning via Planning, Generalization, and Improved Exploration. Junhyuk Oh
2018	J	`jnl`	Generative Adversarial Self-Imitation Learning. CoRR Yijie Guo, Junhyuk Oh, Satinder Singh, Honglak Lee
2018	A*	`conf`	Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies. NeurIPS Sungryull Sohn, Junhyuk Oh, Honglak Lee
2018	J	`jnl`	Many-Goals Reinforcement Learning. CoRR Vivek Veeriah, Junhyuk Oh, Satinder Singh
2018	J	`jnl`	Multitask Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies. CoRR Sungryull Sohn, Junhyuk Oh, Honglak Lee
2018	A*	`conf`	On Learning Intrinsic Rewards for Policy Gradient Methods. NeurIPS Zeyu Zheng, Junhyuk Oh, Satinder Singh
2018	J	`jnl`	On Learning Intrinsic Rewards for Policy Gradient Methods. CoRR Zeyu Zheng, Junhyuk Oh, Satinder Singh
2018	A*	`conf`	Self-Imitation Learning. ICML Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee
2018	J	`jnl`	Self-Imitation Learning. CoRR Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee
2018	J	`jnl`	Unicorn: Continual Learning with a Universal, Off-policy Agent. CoRR Daniel J. Mankowitz, Augustin Zídek, André Barreto, Dan Horgan, Matteo Hessel, John Quan, Junhyuk Oh, Hado van Hasselt, David Silver, Tom Schaul
2017	—	`conf`	Value Prediction Network. NIPS Junhyuk Oh, Satinder Singh, Honglak Lee
2017	J	`jnl`	Value Prediction Network. CoRR Junhyuk Oh, Satinder Singh, Honglak Lee
2017	A*	`conf`	Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning. ICML Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli
2017	J	`jnl`	Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning. CoRR Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli
2016	A*	`conf`	Control of Memory, Active Perception, and Action in Minecraft. ICML Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, Honglak Lee
2016	J	`jnl`	Control of Memory, Active Perception, and Action in Minecraft. CoRR Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, Honglak Lee
2016	A*	`conf`	Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network. CVPR Seunghoon Hong, Junhyuk Oh, Honglak Lee, Bohyung Han
2015	—	`conf`	Action-Conditional Video Prediction using Deep Networks in Atari Games. NIPS Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L. Lewis, Satinder Singh
2015	J	`jnl`	Action-Conditional Video Prediction using Deep Networks in Atari Games. CoRR Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L. Lewis, Satinder Singh
2015	J	`jnl`	Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network. CoRR Seunghoon Hong, Junhyuk Oh, Bohyung Han, Honglak Lee