Julian Schrittwieser

Researcher, DeepMind

Joined

May 2021

Names

Julian Schrittwieser (Preferred)

Emails

****@google.com (Confirmed)

****@deepmind.com (Confirmed)

Personal Links

Homepage

Career & Education History

Researcher

DeepMind (deepmind.com)

Present

Advisors, Relations & Conflicts

No relations added

Expertise

No areas of expertise listed

Publications

StarCraft II Unplugged: Large Scale Offline Reinforcement Learning
Michael Mathieu, Sherjil Ozair, Srivatsan Srinivasan, Caglar Gulcehre, Shangtong Zhang, Ray Jiang, Tom Le Paine, Konrad Zolna, Richard Powell, Julian Schrittwieser, David Choi, Petko Georgiev, Daniel Kenji Toyama, Aja Huang, Roman Ring, Igor Babuschkin, Timo Ewalds, Mahyar Bordbar, Sarah Henderson, Sergio Gómez Colmenarejo et al. (4 additional authors not shown)
- 12 Oct 2021 (modified: 05 May 2023)
- Deep RL Workshop NeurIPS 2021
- Readers: Everyone
Planning in Stochastic Environments with a Learned Model
Ioannis Antonoglou, Julian Schrittwieser, Sherjil Ozair, Thomas K Hubert, David Silver
- Published: 28 Jan 2022, Last Modified: 13 Feb 2023
- ICLR 2022 Spotlight
- Readers: Everyone
Procedural generalization by planning with self-supervised world models
Ankesh Anand, Jacob C Walker, Yazhe Li, Eszter Vértes, Julian Schrittwieser, Sherjil Ozair, Theophane Weber, Jessica B Hamrick
- Published: 28 Jan 2022, Last Modified: 13 Feb 2023
- ICLR 2022 Poster
- Readers: Everyone
Policy improvement by planning with Gumbel
Ivo Danihelka, Arthur Guez, Julian Schrittwieser, David Silver
- Published: 28 Jan 2022, Last Modified: 13 Feb 2023
- ICLR 2022 Spotlight
- Readers: Everyone
Online and Offline Reinforcement Learning by Planning with a Learned Model
Julian Schrittwieser, Thomas K Hubert, Amol Mandhane, Mohammadamin Barekatain, Ioannis Antonoglou, David Silver
- Published: 09 Nov 2021, Last Modified: 26 May 2025
- NeurIPS 2021 Spotlight
- Readers: Everyone

Co-Authors

View all 36 co-authors

Julian Schrittwieser

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

StarCraft II Unplugged: Large Scale Offline Reinforcement Learning

Planning in Stochastic Environments with a Learned Model

Procedural generalization by planning with self-supervised world models

Policy improvement by planning with Gumbel

Online and Offline Reinforcement Learning by Planning with a Learned Model

Co-Authors