Junhyuk Oh - AI Profile

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DeepMind

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I am a research scientist at DeepMind. I finished my Ph.D. at the University of Michigan, where I was co-advised by Honglak Lee and Satinder Singh. My research focuses on deep reinforcement learning. Some of my work has been covered by MIT Technology Review, Daily Mail, and VentureBeat.

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Balancing Constraints and Rewards with Meta-Gradient D4PG

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

ICLR, (2021)

EIBibtex

Introducing Symmetries to Black Box Meta Reinforcement Learning

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

Bibtex

Discovering Reinforcement Learning Algorithms

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

NIPS 2020, (2020)

Cited by12EIBibtex

Meta-Gradient Reinforcement Learning with an Objective Discovered Online

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

NIPS 2020, (2020)

Cited by5EIBibtex

What Can Learned Intrinsic Rewards Capture

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

ICML, pp.11436-11446, (2020)

Cited by9EIBibtex

A Self-Tuning Actor-Critic Algorithm

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

NIPS 2020, (2020)

Cited by4EIBibtex

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

NATURE, no. 7782 (2019): 350-+

Cited by697WOSBibtex

Contingency-Aware Exploration in Reinforcement Learning

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

international conference on learning representations, (2019)

Cited by30EIBibtex

Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies

Sungryull Sohn,Junhyuk Oh,Honglak Lee

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), (2019): 7156-7166

Cited by27EIBibtex

Discovery of Useful Questions as Auxiliary Tasks

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

NeurIPS, pp.9306-9317, (2019)

Cited by2EIBibtex

On Learning Intrinsic Rewards for Policy Gradient Methods

Zeyu Zheng,Junhyuk Oh,Satinder Singh

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), (2018): 4644-4654

Cited by36EIBibtex

Generative Adversarial Self-Imitation Learning

Yijie Guo,Junhyuk Oh,Satinder Singh,Honglak Lee

arXiv: Learning, (2018)

Cited by17EIBibtex

Many-Goals Reinforcement Learning

Vivek Veeriah,Junhyuk Oh,Satinder Singh

CoRR, (2018)

EIBibtex

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

arXiv: Learning, (2018)

Cited by27EIBibtex

Neural Task Graph Execution

Sungryull Sohn,Junhyuk Oh,Honglak Lee

(2018)

Bibtex

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

(2018)

Bibtex

Value Prediction Network

Junhyuk Oh,Satinder Singh,Honglak Lee

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 30 (NIPS 2017), (2017)

Cited by189EIBibtex

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

Junhyuk Oh,Satinder P. Singh,Honglak Lee,Pushmeet Kohli

ICML, (2017)

Cited by156EIBibtex

Learning transferrable knowledge for semantic segmentation with deep convolutional neural network

Seunghoon Hong,Junhyuk Oh, Honglak Lee, Bohyung Han

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.3204-3212, (2016)

Cited by134Bibtex

Action-Conditional Video Prediction using Deep Networks in Atari Games

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

Annual Conference on Neural Information Processing Systems, (2015): 2863-2871

Cited by674EIBibtex

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