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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
5177*2019
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ...
arXiv preprint arXiv:2312.11805, 2023
14902023
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
10222015
Value prediction network
J Oh, S Singh, H Lee
Advances in neural information processing systems 30, 2017
3972017
Control of memory, active perception, and action in minecraft
J Oh, V Chockalingam, H Lee
International conference on machine learning, 2790-2799, 2016
3722016
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
M Reid, N Savinov, D Teplyashin, D Lepikhin, T Lillicrap, J Alayrac, ...
arXiv preprint arXiv:2403.05530, 2024
3582024
Self-imitation learning
J Oh, Y Guo, S Singh, H Lee
International conference on machine learning, 3878-3887, 2018
3582018
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
3172017
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
2212016
On learning intrinsic rewards for policy gradient methods
Z Zheng, J Oh, S Singh
Advances in Neural Information Processing Systems 31, 2018
2112018
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
1532020
Hierarchical reinforcement learning for zero-shot generalization with subtask dependencies
S Sohn, J Oh, H Lee
Advances in neural information processing systems 31, 2018
1062018
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
952019
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
942018
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
922020
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
862020
In-context reinforcement learning with algorithm distillation
M Laskin, L Wang, J Oh, E Parisotto, S Spencer, R Steigerwald, ...
arXiv preprint arXiv:2210.14215, 2022
852022
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
782020
Generative adversarial self-imitation learning
Y Guo, J Oh, S Singh, H Lee
arXiv preprint arXiv:1812.00950, 2018
622018
Many-goals reinforcement learning
V Veeriah, J Oh, S Singh
arXiv preprint arXiv:1806.09605, 2018
572018
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