Publications

Gemini: A Family of Highly Capable Multimodal Models

Gemini Team
Paper

Deep Reinforcement Learning with Plasticity Injection

Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, André Barreto
Paper

In-context Reinforcement Learning with Algorithm Distillation

Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih
Paper

Introducing Symmetries to Black Box Meta Reinforcement Learning

Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram Friesen, Junhyuk Oh, Yutian Chen
Paper

Discovery of Options via Meta-Learned Subgoals

Vivek Veeriah, Tom Zahavy, Matteo Hessel, Zhongwen Xu, Junhyuk Oh, Iurii Kemaev, Hado van Hasselt, David Silver, Satinder Singh
Paper

Balancing Constraints and Rewards with Meta-Gradient D4PG

Dan A. Calian, Daniel J Mankowitz, Tom Zahavy, Zhongwen Xu, Junhyuk Oh, Nir Levine, Timothy Mann
Paper

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

Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu, Dhruva Tirumala, Junhyuk Oh, Gauthier Gidel, Hado van Hasselt, David Balduzzi
Paper

Discovering Reinforcement Learning Algorithms

Junhyuk Oh, Matteo Hessel, Wojciech M. Czarnecki, Zhongwen Xu, Hado van Hasselt, Satinder Singh, David Silver
Paper Press: VentureBeat Press: Analytics India Press: SingularityHub

Meta-Gradient Reinforcement Learning with an Objective Discovered Online

Zhongwen Xu, Hado van Hasselt, Matteo Hessel, Junhyuk Oh, Satinder Singh, David Silver
Paper

A Self-Tuning Actor-Critic Algorithm

Tom Zahavy, Zhongwen Xu, Vivek Veeriah, Matteo Hessel, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
Paper

What Can Learned Intrinsic Rewards Capture?

Zeyu Zheng, Junhyuk Oh, Matteo Hessel, Zhongwen Xu, Manuel Kroiss, Hado van Hasselt, David Silver, Satinder Singh
Paper

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, Manuel Kroiss, Ivo Danihelka, Aja Huang, Laurent Sifre, Trevor Cai, John P Agapiou, Max Jaderberg, Alexander S Vezhnevets, Rémi Leblond, Tobias Pohlen, Valentin Dalibard, David Budden, Yury Sulsky, James Molloy, Tom L Paine, Caglar Gulcehre, Ziyu Wang, Tobias Pfaff, Yuhuai Wu, Roman Ring, Dani Yogatama, Dario Wünsch, Katrina McKinney, Oliver Smith, Tom Schaul, Timothy Lillicrap, Koray Kavukcuoglu, Demis Hassabis, Chris Apps, David Silver
Paper

Discovery of Useful Questions as Auxiliary Tasks

Vivek Veeriah, Matteo Hessel, Zhongwen Xu, Richard Lewis, Janarthanan Rajendran, Junhyuk Oh, Hado van Hasselt, David Silver, Satinder Singh
Paper

Unicorn: Continual Learning with a Universal, Off-policy Agent

Daniel J. Mankowitz, Augustin Žídek, André Barreto, Dan Horgan, Matteo Hessel, John Quan, Junhyuk Oh, Hado van Hasselt, David Silver, Tom Schaul
Paper

Contingency-Aware Exploration in Reinforcement Learning

Jongwook Choi, Yijie Guo, Marcin Moczulski, Junhyuk Oh, Neal Wu, Mohammad Norouzi, Honglak Lee
Paper

On Learning Intrinsic Rewards for Policy Gradient Methods

Zeyu Zheng, Junhyuk Oh, Satinder Singh
Paper Code

Hierarchical Reinforcement Learning for Zero-shot Generalization with Subtask Dependencies

Sungryull Sohn, Junhyuk Oh, Honglak Lee
Paper

Many-Goals Reinforcement Learning

Vivek Veeriah, Junhyuk Oh, Satinder Singh
Paper

Generative Adversarial Self-Imitation Learning

Yijie Guo, Junhyuk Oh, Satinder Singh, Honglak Lee
Paper

Self-Imitation Learning

Junhyuk Oh, Yijie Guo, Satinder Singh, Honglak Lee
Paper Code

Value Prediction Network

Junhyuk Oh, Satinder Singh, Honglak Lee
Paper Code

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

Junhyuk Oh, Satinder Singh, Honglak Lee, Pushmeet Kohli
Paper Video

Control of Memory, Active Perception, and Action in Minecraft

Junhyuk Oh, Valliappa Chockalingam, Satinder Singh, Honglak Lee
Paper Code Video Press: MIT Technology Review Press: Daily Mail

Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network

Seunghoon Hong, Junhyuk Oh, Bohyung Han, Honglak Lee
Paper Code Project

Action-Conditional Video Prediction using Deep Networks in Atari Games

Junhyuk Oh, Xiaoxiao Guo, Honglak Lee, Richard Lewis, Satinder Singh
Paper Code Video