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Junhyuk Oh
Junhyuk Oh
Research Scientist, DeepMind
Zweryfikowany adres z google.com - Strona główna
Tytuł
Cytowane przez
Cytowane przez
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Grandmaster level in StarCraft II using multi-agent reinforcement learning
O Vinyals, I Babuschkin, WM Czarnecki, M Mathieu, A Dudzik, J Chung, ...
Nature 575 (7782), 350-354, 2019
3270*2019
Action-conditional video prediction using deep networks in atari games
J Oh, X Guo, H Lee, RL Lewis, S Singh
Advances in neural information processing systems 28, 2015
8772015
Control of memory, active perception, and action in minecraft
J Oh, V Chockalingam, H Lee
International conference on machine learning, 2790-2799, 2016
3222016
Value prediction network
J Oh, S Singh, H Lee
Advances in neural information processing systems 30, 2017
3192017
Self-imitation learning
J Oh, Y Guo, S Singh, H Lee
International Conference on Machine Learning, 3878-3887, 2018
2502018
Zero-shot task generalization with multi-task deep reinforcement learning
J Oh, S Singh, H Lee, P Kohli
International Conference on Machine Learning, 2661-2670, 2017
2482017
Learning transferrable knowledge for semantic segmentation with deep convolutional neural network
S Hong, J Oh, H Lee, B Han
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
1892016
On learning intrinsic rewards for policy gradient methods
Z Zheng, J Oh, S Singh
Advances in Neural Information Processing Systems 31, 2018
1522018
Discovering reinforcement learning algorithms
J Oh, M Hessel, WM Czarnecki, Z Xu, HP van Hasselt, S Singh, D Silver
Advances in Neural Information Processing Systems 33, 1060-1070, 2020
822020
Hierarchical reinforcement learning for zero-shot generalization with subtask dependencies
S Sohn, J Oh, H Lee
Advances in neural information processing systems 31, 2018
76*2018
Discovery of useful questions as auxiliary tasks
V Veeriah, M Hessel, Z Xu, J Rajendran, RL Lewis, J Oh, HP van Hasselt, ...
Advances in Neural Information Processing Systems 32, 2019
742019
Contingency-aware exploration in reinforcement learning
J Choi, Y Guo, M Moczulski, J Oh, N Wu, M Norouzi, H Lee
arXiv preprint arXiv:1811.01483, 2018
692018
What can learned intrinsic rewards capture?
Z Zheng, J Oh, M Hessel, Z Xu, M Kroiss, H Van Hasselt, D Silver, S Singh
International Conference on Machine Learning, 11436-11446, 2020
542020
A self-tuning actor-critic algorithm
T Zahavy, Z Xu, V Veeriah, M Hessel, J Oh, HP van Hasselt, D Silver, ...
Advances in neural information processing systems 33, 20913-20924, 2020
532020
Meta-gradient reinforcement learning with an objective discovered online
Z Xu, HP van Hasselt, M Hessel, J Oh, S Singh, D Silver
Advances in Neural Information Processing Systems 33, 15254-15264, 2020
502020
Many-goals reinforcement learning
V Veeriah, J Oh, S Singh
arXiv preprint arXiv:1806.09605, 2018
462018
Generative adversarial self-imitation learning
Y Guo, J Oh, S Singh, H Lee
arXiv preprint arXiv:1812.00950, 2018
412018
Unicorn: Continual learning with a universal, off-policy agent
DJ Mankowitz, A Žídek, A Barreto, D Horgan, M Hessel, J Quan, J Oh, ...
arXiv preprint arXiv:1802.08294, 2018
392018
Discovery of options via meta-learned subgoals
V Veeriah, T Zahavy, M Hessel, Z Xu, J Oh, I Kemaev, HP van Hasselt, ...
Advances in Neural Information Processing Systems 34, 29861-29873, 2021
202021
Introducing symmetries to black box meta reinforcement learning
L Kirsch, S Flennerhag, H van Hasselt, A Friesen, J Oh, Y Chen
Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7202-7210, 2022
162022
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