Oh, Junhyuk

Grandmaster level in StarCraft II using multi-agent reinforcement learning

Vinyals, O., Babuschkin, I., Czarnecki, W. M., Mathieu, M., Dudzik, A., Chung, J., Choi, D. H., Powell, R., Ewalds, T., Georgiev, P., et al. (2019) · Nature

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 3,455

Gemini: A Family of Highly Capable Multimodal Models

Gemini Team, Anil, R., Borgeaud, S., Alayrac, J.-B., Yu, J., Soricut, R., Schalkwyk, J., Dai, A. M., Hauth, A., Millican, K., et al. (2023) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 990

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Gemini Team, Georgiev, P., Lei, V. I., Burnell, R., Bai, L., Gulati, A., Tanzer, G., Vincent, D., Pan, Z., Wang, S., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 306

In-context Reinforcement Learning with Algorithm Distillation

Laskin, M., Wang, L., Oh, J., Parisotto, E., Spencer, S., Steigerwald, R., Strouse, D., Hansen, S., Filos, A., Brooks, E., et al. (2022) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 14

Deep Reinforcement Learning with Plasticity Injection

Nikishin, E., Oh, J., Ostrovski, G., Lyle, C., Pascanu, R., Dabney, W., & Barreto, A. (2023) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 4

Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity

Garnelo, M., Czarnecki, W. M., Liu, S., Tirumala, D., Oh, J., Gidel, G., van Hasselt, H., & Balduzzi, D. (2021) · arXiv

Artificial Intelligence in GamesEvolutionary Algorithms and Applications

Cited by 3