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Junhyuk Oh

DeepMind

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My research focuses on deep reinforcement learning. Some of my work has been covered by MIT Technology Review and Daily Mail.

Awards and Honors
Graduate Scholarship from Kwanjeong Educational Foundation, 2014 - 2018
Undergraduate Scholarship from Korea Student Aid Foundation (KOSAF), 2007 - 2014

Papers19 papers

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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, (2021)

Bibtex

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)

EIBibtex

Discovering Reinforcement Learning Algorithms

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

NIPS 2020, (2020)

Cited by2EIBibtex

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)

EIBibtex

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, pp.1-5, (2019)

Cited by589WOSBibtex

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 by25EIBibtex

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, (2019)

EIBibtex

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

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

(2018)

Bibtex

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 by11EIBibtex

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), (2018): 7156-7166

Cited by10EIBibtex

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 by3EIBibtex

Neural Task Graph Execution

Sungryull Sohn,Junhyuk Oh, Honglak Lee

(2018)

Bibtex

Value Prediction Network

Junhyuk Oh,Satinder Singh,Honglak Lee

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

Cited by139EIBibtex

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

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

ICML, (2017)

Cited by111EIBibtex

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 by596EIBibtex

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