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Junhyuk Oh
Junhyuk Oh
Research Scientist, DeepMind
Bestätigte E-Mail-Adresse bei google.com - Startseite
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Zitiert von
Jahr
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
5416*2019
Gemini: a family of highly capable multimodal models
G Team, R Anil, S Borgeaud, JB Alayrac, J Yu, R Soricut, J Schalkwyk, ...
arXiv preprint arXiv:2312.11805, 2023
21832023
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
10402015
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ...
arXiv preprint arXiv:2403.05530, 2024
6842024
Value prediction network
J Oh, S Singh, H Lee
Advances in neural information processing systems 30, 2017
4142017
Control of memory, active perception, and action in minecraft
J Oh, V Chockalingam, H Lee
International conference on machine learning, 2790-2799, 2016
3762016
Self-imitation learning
J Oh, Y Guo, S Singh, H Lee
International conference on machine learning, 3878-3887, 2018
3732018
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
3212017
On learning intrinsic rewards for policy gradient methods
Z Zheng, J Oh, S Singh
Advances in Neural Information Processing Systems 31, 2018
2232018
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
2222016
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
1652020
Hierarchical reinforcement learning for zero-shot generalization with subtask dependencies
S Sohn, J Oh, H Lee
Advances in neural information processing systems 31, 2018
1102018
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
1052022
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
962019
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
952020
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
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
902020
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
832020
Generative adversarial self-imitation learning
Y Guo, J Oh, S Singh, H Lee
arXiv preprint arXiv:1812.00950, 2018
632018
Many-goals reinforcement learning
V Veeriah, J Oh, S Singh
arXiv preprint arXiv:1806.09605, 2018
582018
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