Junhyuk Oh

According to our database, Junhyuk Oh authored at least 28 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Preference Optimization as Probabilistic Inference.

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

CoRR, 2024

2023

Deep Reinforcement Learning with Plasticity Injection.

Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, André Barreto

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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 A. Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Introducing Symmetries to Black Box Meta Reinforcement Learning.

Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Discovery of Options via Meta-Learned Subgoals.

Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Balancing Constraints and Rewards with Meta-Gradient D4PG.

Dan A. Calian, Daniel J. Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy A. Mann

Proceedings of the 9th International Conference on Learning Representations, 2021

Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity.

Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu, Dhruva Tirumala, Junhyuk Oh, Gauthier Gidel, Hado van Hasselt, David Balduzzi

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

2020

Self-Tuning Deep Reinforcement Learning.

Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh

CoRR, 2020

A Self-Tuning Actor-Critic Algorithm.

Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Meta-Gradient Reinforcement Learning with an Objective Discovered Online.

Zhongwen Xu, Hado Philip van Hasselt, Matteo Hessel, Junhyuk Oh, Satinder Singh, David Silver

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Discovering Reinforcement Learning Algorithms.

Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado van Hasselt, Satinder Singh, David Silver

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

What Can Learned Intrinsic Rewards Capture?

Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Grandmaster level in StarCraft II using multi-agent reinforcement learning.

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

Nat., 2019

Discovery of Useful Questions as Auxiliary Tasks.

Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Janarthanan Rajendran, Richard L. Lewis, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Contingency-Aware Exploration in Reinforcement Learning.

Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu, Mohammad Norouzi, Honglak Lee

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Efficient Deep Reinforcement Learning via Planning, Generalization, and Improved Exploration.

Junhyuk Oh

PhD thesis, 2018

Generative Adversarial Self-Imitation Learning.

Yijie Guo, Junhyuk Oh, Satinder Singh, Honglak Lee

CoRR, 2018

Multitask Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies.

Sungryull Sohn, Junhyuk Oh, Honglak Lee

CoRR, 2018

Many-Goals Reinforcement Learning.

Vivek Veeriah, Junhyuk Oh, Satinder Singh

CoRR, 2018

Unicorn: Continual Learning with a Universal, Off-policy Agent.

Daniel J. Mankowitz, Augustin Zídek, André Barreto, Dan Horgan, Matteo Hessel, John Quan, Junhyuk Oh, Hado van Hasselt, David Silver, Tom Schaul

CoRR, 2018

On Learning Intrinsic Rewards for Policy Gradient Methods.

Zeyu Zheng, Junhyuk Oh, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies.

Sungryull Sohn, Junhyuk Oh, Honglak Lee

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Self-Imitation Learning.

Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Value Prediction Network.

Junhyuk Oh, Satinder Singh, Honglak Lee

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Zero-Shot Task Generalization with Multi-Task Deep Reinforcement Learning.

Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Control of Memory, Active Perception, and Action in Minecraft.

Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, Honglak Lee

Proceedings of the 33nd International Conference on Machine Learning, 2016

Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network.

Seunghoon Hong, Junhyuk Oh, Honglak Lee, Bohyung Han

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

Action-Conditional Video Prediction using Deep Networks in Atari Games.

Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard L. Lewis, Satinder Singh

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015