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2020 – today
- 2024
[i24]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:
Preference Optimization as Probabilistic Inference. CoRR abs/2410.04166 (2024)- 2023
- [c20]Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Stenberg Hansen, Angelos Filos, Ethan A. Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih:
In-context Reinforcement Learning with Algorithm Distillation. ICLR 2023 - [c19]Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, André Barreto:
Deep Reinforcement Learning with Plasticity Injection. NeurIPS 2023 - [i23]Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, André Barreto:
Deep Reinforcement Learning with Plasticity Injection. CoRR abs/2305.15555 (2023) - 2022
- [c18]Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen:
Introducing Symmetries to Black Box Meta Reinforcement Learning. AAAI 2022: 7202-7210 - [i22]Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Hansen, Angelos Filos, Ethan A. Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih:
In-context Reinforcement Learning with Algorithm Distillation. CoRR abs/2210.14215 (2022) - 2021
- [c17]Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu, Dhruva Tirumala, Junhyuk Oh, Gauthier Gidel, Hado van Hasselt, David Balduzzi:
Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity. AAMAS 2021: 1501-1503 - [c16]Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A. Mann:
Balancing Constraints and Rewards with Meta-Gradient D4PG. ICLR 2021 - [c15]Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh:
Discovery of Options via Meta-Learned Subgoals. NeurIPS 2021: 29861-29873 - [i21]Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh:
Discovery of Options via Meta-Learned Subgoals. CoRR abs/2102.06741 (2021) - [i20]Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen:
Introducing Symmetries to Black Box Meta Reinforcement Learning. CoRR abs/2109.10781 (2021) - [i19]Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu, Dhruva Tirumala, Junhyuk Oh, Gauthier Gidel, Hado van Hasselt, David Balduzzi:
Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity. CoRR abs/2110.04041 (2021) - 2020
- [c14]Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh:
What Can Learned Intrinsic Rewards Capture? ICML 2020: 11436-11446 - [c13]Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado van Hasselt, Satinder Singh, David Silver:
Discovering Reinforcement Learning Algorithms. NeurIPS 2020 - [c12]Zhongwen Xu, Hado Philip van Hasselt, Matteo Hessel, Junhyuk Oh, Satinder Singh, David Silver:
Meta-Gradient Reinforcement Learning with an Objective Discovered Online. NeurIPS 2020 - [c11]Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh:
A Self-Tuning Actor-Critic Algorithm. NeurIPS 2020 - [i18]Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh:
Self-Tuning Deep Reinforcement Learning. CoRR abs/2002.12928 (2020) - [i17]Zhongwen Xu, Hado van Hasselt, Matteo Hessel, Junhyuk Oh, Satinder Singh, David Silver:
Meta-Gradient Reinforcement Learning with an Objective Discovered Online. CoRR abs/2007.08433 (2020) - [i16]Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado van Hasselt, Satinder Singh, David Silver:
Discovering Reinforcement Learning Algorithms. CoRR abs/2007.08794 (2020) - [i15]Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A. Mann:
Balancing Constraints and Rewards with Meta-Gradient D4PG. CoRR abs/2010.06324 (2020)
2010 – 2019
- 2019
- [j1]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:
Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nat. 575(7782): 350-354 (2019) - [c10]Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu, Mohammad Norouzi, Honglak Lee:
Contingency-Aware Exploration in Reinforcement Learning. ICLR (Poster) 2019 - [c9]Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Janarthanan Rajendran, Richard L. Lewis, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh:
Discovery of Useful Questions as Auxiliary Tasks. NeurIPS 2019: 9306-9317 - [i14]Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Richard L. Lewis, Janarthanan Rajendran, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh:
Discovery of Useful Questions as Auxiliary Tasks. CoRR abs/1909.04607 (2019) - [i13]Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh:
What Can Learned Intrinsic Rewards Capture? CoRR abs/1912.05500 (2019) - 2018
- [b1]Junhyuk Oh:
Efficient Deep Reinforcement Learning via Planning, Generalization, and Improved Exploration. University of Michigan, USA, 2018 - [c8]Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee:
Self-Imitation Learning. ICML 2018: 3875-3884 - [c7]Zeyu Zheng, Junhyuk Oh, Satinder Singh:
On Learning Intrinsic Rewards for Policy Gradient Methods. NeurIPS 2018: 4649-4659 - [c6]Sungryull Sohn, Junhyuk Oh, Honglak Lee:
Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies. NeurIPS 2018: 7156-7166 - [i12]Daniel J. Mankowitz, Augustin Zídek, André Barreto, Dan Horgan, Matteo Hessel, John Quan, Junhyuk Oh, Hado van Hasselt, David Silver, Tom Schaul:
Unicorn: Continual Learning with a Universal, Off-policy Agent. CoRR abs/1802.08294 (2018) - [i11]Zeyu Zheng, Junhyuk Oh, Satinder Singh:
On Learning Intrinsic Rewards for Policy Gradient Methods. CoRR abs/1804.06459 (2018) - [i10]Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee:
Self-Imitation Learning. CoRR abs/1806.05635 (2018) - [i9]Vivek Veeriah, Junhyuk Oh, Satinder Singh:
Many-Goals Reinforcement Learning. CoRR abs/1806.09605 (2018) - [i8]Sungryull Sohn, Junhyuk Oh, Honglak Lee:
Multitask Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies. CoRR abs/1807.07665 (2018) - [i7]Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu, Mohammad Norouzi, Honglak Lee:
Contingency-Aware Exploration in Reinforcement Learning. CoRR abs/1811.01483 (2018) - [i6]Yijie Guo, Junhyuk Oh, Satinder Singh, Honglak Lee:
Generative Adversarial Self-Imitation Learning. CoRR abs/1812.00950 (2018) - 2017
- [c5]Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli:
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning. ICML 2017: 2661-2670 - [c4]Junhyuk Oh, Satinder Singh, Honglak Lee:
Value Prediction Network. NIPS 2017: 6118-6128 - [i5]Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli:
Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning. CoRR abs/1706.05064 (2017) - [i4]Junhyuk Oh, Satinder Singh, Honglak Lee:
Value Prediction Network. CoRR abs/1707.03497 (2017) - 2016
- [c3]Seunghoon Hong, Junhyuk Oh, Honglak Lee, Bohyung Han:
Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network. CVPR 2016: 3204-3212 - [c2]Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, Honglak Lee:
Control of Memory, Active Perception, and Action in Minecraft. ICML 2016: 2790-2799 - [i3]Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, Honglak Lee:
Control of Memory, Active Perception, and Action in Minecraft. CoRR abs/1605.09128 (2016) - 2015
- [c1]Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L. Lewis, Satinder Singh:
Action-Conditional Video Prediction using Deep Networks in Atari Games. NIPS 2015: 2863-2871 - [i2]Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L. Lewis, Satinder Singh:
Action-Conditional Video Prediction using Deep Networks in Atari Games. CoRR abs/1507.08750 (2015) - [i1]Seunghoon Hong, Junhyuk Oh, Bohyung Han, Honglak Lee:
Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network. CoRR abs/1512.07928 (2015)
Coauthor Index
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